Help PhDs to kick-start careers in industry | Co-Founder and CEO @Alma.me | Building a bridge between academia and industry | Speaker | Scientist

Welcome to my profile!

I'm Elena, passionate about helping PhDs kickstart fulfilling careers outside of academia, and connect them with industry relevant positions. 

During my PhD journey, I realized that many PhDs face challenges transitioning from academia to industry. This difficulty often arises due to a lack of knowledge about potential positions, how to craft a resume for the industry, and prepare effectively for a job in that sector.

I've experienced this struggle firsthand. While pursuing my PhD, I felt lost. I knew that I no longer wanted to work in the lab; instead, I wanted to work with people, as that's where my passion lies. I went on my own discovery journey on "what is next".  I focused on the things I loved doing and thought of possible career options- after I identified what is next- I started working toward it by building a network in that area. 

Who am I, and how did I get here?

I recently graduated with a PhD in Medical Sciences from the Karolinska Institutet in beautiful Stockholm. 
As a Co-Founder and CEO of Alma.me my vision is to bridge the gap between academia and industry by providing information to help PhDs understand the array of opportunities after completing their studies and recognise the value of their skills beyond academia. 

If you are a PhD-student, Postdoc or tenure and you want to make the transition into industry follow me for more career advice.


Elena Hoffer, PhD

"If you care too much about money, you're not truly committed." 

This sentence from Dritjon Gruda in the latest Career Nature Magazine captures a mindset that’s deeply embedded in academia - and a big reason why scientists rarely talk openly about money. 

Many academics believe that asking for fair pay makes them look less committed to science. As if caring about your livelihood somehow cancels out your passion. 

Over the years, I’ve met senior academics who never negotiated their salary in their life. 

I’ve also met researchers who couldn’t afford to live near their lab because it would eat up half their salary. 

And often, this is accepted. 

Because science is framed not as a job - but as a calling. Something you do out of passion, not for stability or comfort. Talking about wanting to make enough money to live a comfortable life should be normalised in academia!

During my PhD, when I said I wanted to move into industry, the first response I got was: 
“Oh… so you’re going for the money?” 

That question made me feel terrible. 
But why? 

What is wrong with wanting a comfortable life and meaningful work? 

The article helped spark this reflection - and I hope that for the next generation of scientists, this mindset starts to shift. 

If we want scientists to worry less and focus on what they are good at - doing science - we need to make them feel financially secure.

I’ll link the article in the comments 👇

♻️  Repost to help a friend

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Help PhDs to kick-start careers outside of academia | CEO @Alma.me | Complementing universities services for PhDs & Postdocs to secure jobs outside academia | Speaker I Podcast Host @PostPhDirections

I didn’t leave academia because I don’t love science.
I love science deeply.

I would say most people don’t leave because they stop being curious or scientifically driven. They leave because the way the system is designed doesn’t serve them anymore.

Being a “successful” scientist often comes with enormous sacrifices: long working hours, weekends in the lab, nights that blur into mornings. Life is frequently put on hold. And after all that, you still find yourself wondering whether you can afford a nice dinner with friends.

The hardest part? 
After years of sacrifice, there is no guarantee of a career in academia. It’s a high-risk investment. Only a small fraction will make it - often not just the best scientists, but those with the right timing, networks, or luck. 
Everyone else eventually has to leave.

Leaving academia is not a failure. But for many, it feels like finally allowing themselves to pursue a life they’ve been postponing for years.

- Kids can wait until after my postdoc.
- Getting married doesn’t fit right now.
- Buying a home feels impossible while moving countries every few years.

While others move forward with their lives, an academic career often asks you to keep waiting. And even when you “succeed,” it can come at a very high personal cost.

I left because the system no longer aligned with my values. 
And I think this is true for many academics.

Wanting to have more stability is a valid reason to leave - even if you love what you do 💙

Your PhD ≠ one career path.

One of the biggest misconceptions I had during my PhD was that my options were academia — or R&D in industry.

After all, I had spent years at the bench.

What I didn’t realise at the time was that my PhD had given me far more than lab techniques - and that many industry roles value those skills far beyond bench work.

Here’s a simple way to think about industry roles for PhDs ⬇️

If you enjoy coding & working with numbers
 → Data Scientist · Data Analyst · Decision Scientist

If you enjoy discovering or building new knowledge
 → Research Scientist · Applied Scientist · R&D

If you enjoy explaining complex ideas clearly
 → Medical Writer · Medical Science Liaison (MSL) · Technical Writer

If you enjoy big-picture thinking & decision-making
 → Product Manager · Strategy Analyst · Consultant

If you enjoy working with customers & real-world problems
 → Technical Sales · Field Application Specialist

What all of these roles have in common?
They value PhD skills: research, analysis, problem-solving, writing, learning fast.

♻️  Share to help a friend 

And if you want to listen to some real transitions stories of PhDs check out my Podcast: PostPhDirections - link in the comments 👇

Many PhDs (and the world) underestimate the skills they’ve developed along the way. 

If you pause and look back to when you started your PhD, think about everything you can do now that you couldn’t do then - from establishing collaborations and managing projects, to writing, problem-solving, ordering reagents, and keeping complex work moving forward. 

A PhD doesn’t just give you technical expertise. 
It builds powerful transferable skills: critical thinking, communication, resilience, and persistence. 

We’ve worked with PhDs who moved from psychology into fintech, from computational neuroscience into medical writing, and from toxicology into project management - all by focusing on these skills rather than their subject area. 

You are more than your PhD topic. 

And your skills can take you further than you think!

♻️  Repost to raise awareness and help another PhD 

Happy Tuesday 🙌

Your PhD is work experience

Is it? 

This is one of the most common questions I get from PhDs who want to transition into industry. 

And I get why it’s confusing. 

We’re trained to think of a PhD as “education.” 

So it feels strange to suddenly call it work experience. 

But here’s the thing: 
Industry doesn’t define work experience as “having a job outside academia.” 

Work experience means: 
• Applying skills 
• Solving real problems 
• Dealing with uncertainty 
• Communicating results 
• Collaborating with others 

For example:
Designing a study, managing timelines, dealing with failed experiments, aligning with collaborators, and presenting outcomes to different audiences - that’s professional experience.

That’s exactly what happens during a PhD. 
You agree?

You don’t just learn about things. 
You do things. 

So yes - your PhD is work experience. 
And it belongs under professional experience in your resume.
 
If you’ve been unsure about this, you’re not doing it wrong. 
You just needed a better definition. 

You’ve got this. 

And if you feel stuck in your transition we can help. Check if our Job Accelerator Program aligns with your needs. Link in the comments 👇 

♻️  Repost to help demystifying what a PhD actually is and does!

There is no single path after a PhD.

Becoming a professor is just one of many possible options. In fact, around 90–95% of PhD graduates move on to roles outside the traditional professorship track — including positions within academia such as administration, staff scientist roles, or facility management.

Outside academia, PhDs transition into industry, government, or NGOs, where they contribute as data scientists, project managers, analysts, scientists, and much more.

The idea that a PhD automatically leads to a career as a professor is outdated. Yet many PhDs are still unaware of the wide range of alternatives, as these paths are rarely discussed within universities.

There is no one “right” path after a PhD — whatever you decide to do is valid

♻️ Repost to help a friend

Happy Saturday 💪

Most interviews ask the same questions:

• Tell me about yourself
• Walk me through your CV
• Why this role / company?
• Salary expectations
• Behavioral + technical questions

Some look simple. But in most cases they aren’t. Many PhDs get lost in academic jargon and detail for 10+ minutes, and this is a recipe for losing your listener.

Interviews rarely test the question itself.
They test what sits underneath it.

Once you understand this, interviews get easier. You’ll realize they’re not interested in every detail of your academic history.

So let's talk about it!

“Tell me about yourself”
→ Can you structure and prioritize information?

“Walk me through your background”
→ Can you translate experience into relevance?

“Why this role / company?”
→ Are you intentional - and do you understand their problems?

“Salary expectations”
→ Do you know your market value?

Behavioral questions test:
→ self-awareness, judgment, communication

Technical questions test:
→ how you think, apply knowledge, handle uncertainty

Here’s what many PhDs miss:
👉 Interviews are not exams.

You’re there to show how you think, communicate, and learn.

If interviews feel stiff or unnatural, it’s often not a skills problem. 

Most often, PhDs feel they have to put on a mask and perform. Once you allow yourself to be yourself, things get easier and more authentic.

And yes - this can be learned. We teach it everyday in our job accelerator program.

You got this 🙌 

♻️ Share to help a friend

Happy Tuesday 🙌

When I was doing my PhD, I thought networking was really awkward.
I didn’t like it, and honestly, I didn’t really know how to do it.

Looking back, most of that resistance came from the fact that I completely misunderstood what networking actually is.

Once I reframed it, everything changed.

I stopped thinking about networking as asking people for favors or jobs and started seeing it for what it really is: relationship building.

That shift alone helped me build both a global online network and a local, in-person one.

So how did I actually get started on LinkedIn?

Very simply. But still very uncomfortable
 
I looked for people who shared similar interests to mine - in my case, other founders and PhDs.

I commented on their posts. I engaged with their ideas.
And by showing up consistently, relationships started to form.

Some of those people I later met for an online coffee chat.
Some I’ve collaborated and partnered with.
Some I’ll probably meet in the future.

And with others, we might simply stay “LinkedIn friends” — and that’s perfectly fine too.

The key is this: find a point of connection and engage around it regularly.
The basis of any real relationship is trust - and trust is built by showing up, again and again.

My biggest tip?
Go into every conversation with curiosity, not expectation.

Does that mean you shouldn’t have a strategy? 
Absolutely not.

But what I’ve learned is that when you follow your genuine interests, you naturally connect with people who care about the same things.

For example, I’ve built a strong network with many PhDs here on LinkedIn.

Some create content on similar topics, others on completely different ones - but what connects us is that we all want to support PhDs: some during their PhD journey, others in their careers beyond academia.

That shared mission makes conversations easy and meaningful.

If you’re not sure where to start, ask yourself:
What topics am I genuinely excited about professionally?

Then start connecting. 
Start commenting.

And if you’re stuck wondering what to comment, here are a few easy options:
- Share your perspective
- Add your own experience
- Contribute an additional insight or resource

Whatever it is - just get started.
That’s how relationships (and networks) are built.

What began as me figuring this out for myself is now what I do every day with PhDs who want to move into industry.

If networking, positioning yourself, or breaking into industry feels unclear -
 you’re not alone.

Curious how we support PhDs at Alma.Me? You can learn more on our website.

Happy Tuesday 🌻

One of the biggest mistakes we see PhDs make in interviews is treating them like an exam.

They focus on saying the right thing.
They memorize answers.
They try to sound impressive.

And in the process, they lose the most important part: the human connection.

An interview is not an exam.
It’s a conversation.

The people interviewing you are human.
And humans hire humans.

What we see again and again in the Alma.Me Job Accelerator Program is this:
PhDs prepare answers by heart.

They sound polished - but also robotic.
There’s no rapport, no flow, no real connection.

And then something interesting happens.
Some candidates come to an interview exhausted.
They’ve had too many interview  so much that they can’t “perform” anymore.

Others walk in thinking:
 “I don’t stand a chance anyway.”

So they stop trying to impress.
They let their guard down.

 They speak naturally.
 They listen.
 They connect.

And that’s often the moment they get hired.
Not because they suddenly became more qualified - but because they finally showed up as themselves and build real connection with the hiring team.

You don’t need to pretend to be an expert.
You already are one.

♻️  Repost to help a friend 

This is exactly what we train PhDs on inside our program: how to stop performing and start connecting in interviews.

👉 If you want to learn this step by step and get coached on it, apply to the Alma.me Job Accelerator Program here: link in the comments

Why reading job descriptions felt impossible as a PhD 

Because as a PhD, I was trained to: 
– Meet every requirement 
– Avoid overclaiming 
– Only apply when fully qualified 

But industry works differently. 
What I learned the hard way: 
Job ads describe an ideal, not a checklist 

- Transferable skills matter more than exact tools 
- You’re evaluated on patterns, not perfection 
- Potential counts - even if no one says it out loud 
- Confidence is read as competence 
- Applying is part of learning, not the final exam 

Through the work I do with Alma.Me I see many PhDs get stuck- just like I did. Thinking you need to match 100% of the description and then get discouraged.

Don't self-reject. I could tell you so many stories of PhDs who thought something was out of reach - they dared and succeeded! 

The perfect candidate does not exist if you meet 70% of the requirements – APPLY  

This shift alone will change the way you approach applications.

♻️  Repost to help a friend 

Happy Wednesday 💙

Academic merits ≠ industry jobs

When PhDs move from academia into industry, they often highlight the same things that opened doors in academia: publications, subject-matter expertise, academic achievements.

That makes sense - it worked in academia.

But in industry, different things are valued.
Hiring managers care less about what you studied and much more about how you work and what were the results and outcomes of your work.

What actually matters:
- How you solve messy, real-world problems
- How you communicate with non-experts
- How you manage projects with unclear outcomes
- How you collaborate, adapt, and keep going when things don’t work

The good news?
You already built these skills during your PhD.

The challenge is this:
 👉 You were trained to talk about knowledge, not outcomes and results. 

If you’re moving into industry, stop asking:
 “Is my research relevant?”

Start asking:
 “Which skills did I use - and how do I show them that I can do the job?”

That shift changes everything.

You got this!!!

♻️  Share to help a friend 

Happy Wednesday 🙌  

---------------
If you want help moving from academic framing to industry-ready positioning, you can check out my website to see how we support PhDs in that process.

I read this article published in The Wall Street Journal and immediately recognized many of the PhDs we work with in it.

Jeremy did everything “right.”
PhD from a strong institution.
In the right city.
In the right industry.

And still: hundreds of applications, no traction, financial pressure, and the growing sense that the path he planned for simply isn’t there anymore.

This is often the moment when PhDs come to us.

Not because they suddenly lost their skills - but because the environment around them changed. 
Funding slows. Hiring freezes spread. Entire ecosystems that once felt stable become unpredictable. And people who were told they were “on a safe path” find themselves questioning everything.

What strikes me about this article is how clearly it shows that this isn’t an individual failure. 
The talent is still there. 
The training is still there. 
What’s missing are the opportunities PhDs were implicitly promised would exist.

Many of the PhDs we work with are in a similar position: they’ve done what they were told would lead to a smooth transition into industry, and yet they’re stuck. 

They read job ads and feel strangely disconnected from them - as if the roles are asking for something they have, but in a language they were never taught to speak.

So they apply more. 
And then more. 
And when that doesn’t work, the self-doubt starts creeping in.

But the problem is rarely a lack of ability. It’s a lack of translation.

Academic training teaches depth, rigor, and independence. 
Industry hiring - especially in a downturn - prioritizes clarity, applicability, and proof of impact. 

When those two worlds don’t align, even very strong PhDs can end up invisible.

Articles like this one are unsettling - but they’re also clarifying. 
They show that relying on a single, linear narrative (“PhD → biotech job → stability”) is risky, not because the PhD is a bad choice, but because markets shift faster than training models do.

For the PhDs who read this and feel anxious or discouraged: that reaction makes sense. You’re responding to real structural changes, not personal shortcomings.

And for many, this is the point where they stop asking “What’s wrong with me?” and start asking “How do I position my skills so they actually make sense outside academia - and across different contexts?”

That shift is often where things begin to move again.

♻️  Share to help a friend 

Want to learn how to align your skills, interests, and values beyond the obvious job choices?

We’re at Alma.Me hosting a free live session where we match PhD skills to industry roles - in real time, with real examples.

Link in the comments 👇

Dear PhDs, rejection is part of the application process....


It’s normal - and yet it stings. It does something to you.
But it says nothing about your personal worth or the value of your skills.

You are not going to be a fit for every position you apply for.
My best recommendation is to expect rejection - because it will come.

But also remember: every no brings you closer to a yes.
And this isn’t theory - it’s what we see over and over again in our job accelerator program where we work with PhDs from various fields.

We had PhDs who went through 17+ interview processes before the yes came.

We had PhDs who made it to the final round - and lost to candidates with more industry experience.

We had PhDs who were promised an offer - and had the position cancelled last minute.

We had PhDs who passed the recruiter screen - but never made it to the hiring manager interview.

And here’s the good news: they all eventually made it.

They turned many no’s into one yes.
Ultimately, you only need one yes - for a position you actually love.

And for most PhDs, the hardest part isn’t competence.
It’s endurance.

If you’re in the middle of this right now and feel like giving up, know this:
your story is not a single one. It’s the story of many PhDs - and it can and will end positive.

👉 If you want structured support to navigate rejections, interviews, and the hiring process as a PhD, apply for our job accelerator program here: 

Happy Monday 🙌

Is doing a PhD worth it?

There are probably as many opinions on this as there are PhDs.

So here’s my take.

Whenever we ask whether a PhD is “worth it”, we first need to ask:
worth it by which criteria?

Are we talking about:
- learning and training?
- financial compensation?
- career optionality?
- status and recognition?

Because depending on what you evaluate, the answer will be very different.

Another important point:
👉 The value of a PhD differs massively by country and industry.

Especially in STEM, PhDs tend to be highly valued in places like the US and Germany - both in perceived status and compensation. 
Over the years, through many conversations, I’ve learned that the same degree can open doors in one country and be almost irrelevant in another.


So let’s break it down.

1. If your goal is an academic career:
Be very clear-eyed about what that means. It’s highly competitive, structurally uncertain, and only a small fraction make it long term.

2. If your goal is growth and learning:
Honestly? I absolutely recommend doing a PhD.
It challenges you in ways few things do. I often describe it as running a small startup: you wear all the hats, constantly problem-solve, deal with failure, and keep going anyway.

If you move countries for your PhD, the growth is even bigger - intellectually and personally.

3. Financial payoff (jobs in industry):
This one depends heavily on field, country, and industry.
We’ve seen PhDs walk into roles paying 150–175k. Others start closer to 100k.
Could you have made more by choosing a different path? Maybe.
But it’s not a simple yes or no.

4. Being a door opener:
Coming from Germany, where education still carries a lot of weight (yes, “Dr.” is literally on your passport), I do think a PhD can still open doors - especially in Pharma and biotech. In some environments, you will hit a glass ceiling without it.

5. Subject-matter expertise:
If you want to deeply immerse yourself in one topic for 4–5 years and truly become an expert - there’s no better way.

6. Mobility:
One of the most underrated perks.
PhDs and postdocs allow you to move internationally, attend global conferences, and work in incredibly international environments.

So is a PhD worth it?
👉 There is no universal answer.

For me personally:
Yes. I would do it again.

I did a PhD in Immunology. I don’t use the subject-matter expertise today - but I do use the skills every single day: grit, creative problem-solving, dealing with failure, trying again.

I still think like a scientist. I approach problems like a scientist.

Is shifting that mindset into industry always easy?

Probably better to ask Angela Priest, my co-founder at Alma.Me - she has 20+ years in business and has been working with me for the past three years 😉

Curious how others see this - was your PhD worth it, and by which criteria?

♻️ Reshare to raise awareness and help a friend

🎙️ New PostPhDirections episode is out!

In this episode, I’m joined by Benjamin Weber Weber,  the Vice President of Translational Research at Novo Nordisk, to unpack what it really takes for PhDs to stand out in today’s competitive pharma job market.

Ben hired PhDs in Pharma in the US, and across different countries in Europe.

This episode is packed with a lot of practical advice on how you can prepare for the transition into Pharma R&D

We talk about:
- How Pharma  hiring has changed - and what skills matter most now
- Why understanding the Pharma R&D value chain is a key differentiator
- Common CV/resume and application mistakes PhDs make (and how to fix them)
- What hiring managers actually look for beyond publications and technical skills

If you’re a PhD or postdoc thinking about (or struggling with) the transition from academia to industry, this episode is packed with practical, honest insights from someone who hires globally.

🎧 Listen to the full episode on Spotify or my new YouTube channel - links in the comments  ⬇️

Happy Friday 🙌

“What should I do after my PhD?” feels often impossible to answer.
There are so many roles out there.

For many PhDs, it’s genuinely overwhelming.

Should I keep doing bench work?
If not — what else can I do?

Over the years, we’ve helped PhDs move into:
- Data Science roles at fintech companies
- Quantitative Modelers at insurance companies
- Project Management roles in healthcare
- Medical writers in Pharma 
…and many more.

The truth is:
You can do a lot after a PhD.
What you can do depends on:
- Your skills
- Your interests
- Your values
- And the kind of life and work situation you want to create

But for most PhDs, the hardest part isn’t having options.
It’s mapping their skills to real industry roles - and understanding what those roles actually look like inside companies.

That’s why we at Alma.Me decided to host a live mapping session where we show you exactly how to approach this in practice.

The session is led by my co-founder Angela Priest. 
She brings over 25 years of industry experience, having hired across all levels and a wide range of roles. Most importantly, she’s seen first-hand how many different roles truly exist inside companies - far beyond what job ads suggest.

📅 Join us for a FREE session on January 15, 6PM CET I 10 AM MST

We’ll map a PhD’s skills and interests to concrete roles in industry.
👉 Sign up here: https://lnkd.in/dVuaRrr4

I finally started something I’ve been thinking about for a long time.

I didn’t start earlier because the perfectionist in me kept holding me back - something I’m actively trying to unlearn from academia (still two years later 😅).

But I finally created my first YouTube video.
It’s not perfect, and that’s okay.

One thing business has taught me: do first, improve later.

So here it is - my first video of many:  Is my PhD work experience?

Each week, I’ll be answering common (and often stressful) questions PhDs and postdocs have about transitioning into industry.

This week’s question:
Does the first job after academia need to be the perfect one?

👉  If this resonates, please hit the subscribe button to the channel. 
I already have a few other videos on the transition from academia to industry - and while it’s not perfect yet, it is authentic.

See you on YouTube: https://lnkd.in/dJbpkcXa

This PhD tried to move to industry since March 2025.
She did what so many PhDs do: applied without any strategy

- 300 applications
- A few interviews
- One final-round interview where she was almost certain she’d get the job

And then the rejection came.

That was the moment she realized something had to change.

Not her skills.
Not her PhD.
But how she was approaching the transition.

She found our Alma.Me Job Accelerator Program through ChatGPT (still one of my favorite stories).

She joined us in September.

In October, she started applying with the resume we built together - one that finally translated her experience into industry language.

What happened next?
Some weeks she had up to 4 interviews.
In November, she accepted a job offer as a Project Manager.

This wasn’t luck.
It was the result of strategy, clarity, and consistent follow-through - exactly what we focus on inside the program.

If you’re applying, interviewing, and still getting stuck at “almost” - you don’t need more applications.

You need clear positioning, honest feedback, and a system that works.

👉 If you’re struggling and want structured support at every step, apply to the Alma.Me Job Accelerator Program. 
Apply here: https://www.alma.me/

Happy Wednesday ✨

Many PhDs primarily consider bench roles when moving into industry.

However, there are alternative career paths for PhDs -  one example is scientific business development.

Yasmine Penn is currently hiring for roles across the US. If this sounds like you, reach out to her 👇

🧬 From the bench to the boardroom - ever considered this path?

For many PhD scientists, moving away from the lab doesn’t mean moving away from science.

Scientific Business Development offers a powerful route into industry for researchers who enjoy big-picture thinking, collaboration, and translating complex science into real-world impact.

We’re currently supporting Scientific Business Development opportunities across the USA, ideal for PhD-level scientists looking to make their first commercial move.

Who this suits:

🔬PhD scientists (Immunology, Pharmacology, Cancer Biology, Genetics or related fields)
🔬Strong hands-on in vivo experience (mouse models)
🔬Curious, commercially minded researchers - no prior BD experience required

Over time, this path builds commercial awareness, client-facing confidence, and cross-functional influence - with a front-row seat to how science becomes products.

📍 Now hiring across multiple US locations
📩 Interested in learning more or applying?
Contact Yasmine Penn
📧 yasmine@greenlsr.com

www.greenlsr.com

#ScientificBusinessDevelopment #PhDJobs #LifeScienceCareers #FromBenchToBusiness #BiotechJobs #CRO #IndustryCareers #GreenLifeScience

It took 6 days. 
 
That's how long it took one of the PhDs I'm working with to land his first interview after he started applying. 
 
What changed? 
-We taught him how to identify and reach out directly to hiring managers 
- We overhauled his resume to focus on impact 
 
He went from: 
 
"Optimized targeted therapies through comprehensive in-vitro testing and data analysis, driving drug viability insights through molecular biology, pharmacokinetics, and chemical analysis." 
 
To: 
 
"Conducted a rapid screening of 50 peptide compounds over a 6-week period for glioblastoma drug discovery, partnering with chemistry, prioritizing and identifying 6 viable compounds for preclinical in vivo testing." 
 
The same person, the same work, but one version shows the impact, the other describes the process. 
 
Hiring teams don't have time to translate your resume. 
 
Do it for them. Make it easy for them to say yes!
 
___________________________ 
 
Are you a PhD struggling to get a job in industry? Check out our job search program here: https://www.alma.me/

Happy Friday 🙌

I help PhDs, Postdocs & Lecturers secure tenure-track jobs and navigate academia | Insider knowledge tips on how to succeed | Academic Career Mentor | Professor & Research Director

I was a lost PhD student. Confused. Overwhelmed. Ready to quit.

Sitting in my tiny office at 2 AM, drowning in research papers, I made a promise...

"If I somehow make it through this, I'll help others navigate what I'm struggling with."

Today, I'm a Professor at a top UK university.

But here's what matters more...

I've kept that promise by helping researchers complete their PhDs and navigate academia.

------

The brutal truth about doing a PhD/DBA whilst working

I hear the same struggles from the 26% of PhD & DBA students who are working professionals:

→ I can't keep up -the mental capacity is exhausted
→ I'm juggling three full-time jobs with no bandwidth
→ I've been stuck for 3-6 months with no real progress
→ My family thinks my PhD/DBA is a hobby, not a second job
→ I feel isolated - no one understands what I'm going through

Sound familiar? You're not alone. And it's not your fault.

Universities train PhD/DBA researchers for academia, but working professionals need something completely different:

❌ You're investing $25-80K but risk joining the 33% who drop out
❌ Motivation crashes after major life events (births, job changes, pandemic)
❌ Distance learning leaves you isolated, struggling to navigate systems alone
❌ You don't have 40 hours/week; you have 10 hours scattered across nights & weekends  
❌ Your supervisor gives great academic feedback but doesn't understand work-life-PhD balance

That's why I created specialised services for serious researchers.

My transformation:

→ 30+ PhDs/DBAs mentored to success
→ 130+ publications across top journals
→ £9 million in research funding secured
→ From PhD uncertainty to Professor by 40
→ 230K researchers follow my guidance daily
→ Research reached 30+ million people globally

FREE RESOURCES:

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My mission:

Help you complete your PhD/DBA on time while using AI responsibly in your research.

Academic success doesn't have to be a mystery. You just need the right guide.

Emmanuel Tsekleves

A PhD student showed at my office in tears. Prof Clarke sent me to you. I can't do this anymore. She wasn't failing her PhD. Her PhD was failing her.

Heather was brilliant. Motivated. Passionate about her research.

But her supervisor was failing her.

Not academically. Emotionally.

That conversation changed how I think about mentorship forever.

Here's what I learned:

Most supervisors focus only on research progress.

They ignore the human being behind the work.

Heather's supervisor was technically excellent.

But emotionally absent.

She didn't need a smarter supervisor.

She needed a more present one.

I started meeting with Heather weekly.

I gave her what was missing:

1) Recognition
I celebrated small wins. Not just problems.
"Your literature review structure is improving" mattered as much as technical feedback.

2) Responsibility
I helped her own her research decisions.
She didn't need permission for every choice.

3) Learning
I created space for questions without judgment.
"I don't understand this" became a starting point. Not a failure.

4) Joy
I reminded her research should excite her.
We discussed ideas over coffee. Not just problems in formal meetings.

The transformation was incredible.

Heather went from wanting to quit to finishing 3 months early.

Her confidence returned. Her research quality improved.

She now supervises her own students using these same principles.

The problem was never Heather's ability.

It was inadequate support.

Your PhD supervisor has more impact on your mental health than your therapist.

Choose them wisely.

And if you're a supervisor reading this:

Your job isn't to push students harder.

It's to support them better.

---

Which of these 4 elements did YOU need most during your PhD?

Recognition, Responsibility, Learning, or Joy?

#PhDLife #AcademicMentorship

I help busy researchers complete their PhDs and DBAs on time | Expert Thesis Reviewer | AI in Research Training for Researchers & Universities | Professor | 200,000+ researchers guided

No alternative text description for this image

"I can't afford a PhD." I hear this every week.
And every week, I show them scholarships they never knew existed.
There are 50+ fully-funded PhD programmes worldwide.

Most students only know about 3-4.

They apply to the same obvious ones.

They compete against thousands.

They get rejected.

Then they assume funding doesn't exist.

It does. They just don't know where to look.

I spent 2 months mapping every major PhD scholarship I could find.

50 programmes across 6 continents.

Here's what surprised me:

→ 7 fully-funded options in North and South America alone
→ 19 programmes across Europe (not just UK and Germany)
→ 16 scholarships in Asia most Western applicants ignore
→ Hidden gems in Africa, Middle East, and Oceania

Some cover tuition only.

Many cover tuition + living expenses + travel.

A few even include family allowances.

The difference between funded and unfunded PhDs isn't talent.

It's knowing where to look.

I've mapped all 50 scholarships by region in the visual below.

Save it. Share it with someone who thinks they can't afford a PhD.

Links to each programme in the comments.

---

Which region are you considering for your PhD?

#PhDScholarships #PhDFunding

Writing Guides

Ready for more? 

Join my exclusive weekly Academic Pathfinder newsletter where I share the exact strategies that have helped hundreds of PhDs finish their PhDs on time, secure competitive tenure-track positions and thrive in academia. 

Get Wednesday's insider tactics delivered straight to your inbox: https://phdtoprof.com/newsletter

Newsletter

Ready for more? 

Join my exclusive weekly PhD Insider newsletter where I share the exact strategies that have helped hundreds of PhDs finish their PhDs on time, use AI responsibly in Research and thrive in academia. 

Get Wednesday's insider tactics delivered straight to your inbox: https://phdtoprof.com/newsletter

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👉 Try for free: https://www.bohrium.com/?utm_source=oversea&utm_term=emmanuel&utm_campaign=kol

PhD 1:1 Autoplug 1 (Form-directed)

Doing your PhD while working full-time is lonely.

Your supervisor is juggling 12+ students. They don't understand how it feels to squeeze research into exhausted evenings and weekends. You get vague feedback like "needs more depth" with no clear direction. Months pass. You start wondering if you'll ever finish.

I've mentored 30+ mid to senior professionals through this exact struggle to successful completion.

20 years at a top 1% university. 25+ PhD examinations. I know where you're losing time.

I take on a small number of dedicated professionals for private premium 1:1 mentorship.

Interested? Start here: https://forms.gle/L3wuDxfAgvDA17SD8

1:1 mentoring Autoplug 2 (Form-directed)

Ready for more? 

Join my exclusive weekly Academic Pathfinder newsletter where I share the exact strategies that have helped hundreds of PhDs finish their PhDs on time, use AI responsibly in Research and thrive in academia. 

Get Wednesday's insider tactics delivered straight to your inbox: https://phdtoprof.com/newsletter

1:1 Mentoring Autoplug 3 (DM-directed)

You're trying to do three jobs at once: career, family, PhD.

Your supervisor has never lived that reality. I have spent 20 years mentoring professionals who have.

Private premium 1:1 mentorship for mid to senior professionals serious about finishing. Limited availability.

DM "MENTORSHIP" with your PhD stage and biggest challenge right now.


1:1 Mentoring Autoplug 4 (DM-directed, shortest)

Feeling behind on your PhD? Supervisor too busy to help? Wondering if you'll ever finish?

I provide private premium mentorship for mid to senior working professionals. 1:1 support. Limited spots.

DM "MENTORSHIP" with your situation.


My student cut her literature review from 4 months to 6 weeks.
Same number of papers. Same quality. Half the time.
She didn't work harder. She switched tools.

My PhD student was drowning in 200+ papers.

She spent 6 hours a day just reading and organising.

No time left for actual writing.

I introduced her to 5 tools.

Within a month, she cut her literature review time in half.

Here's what I've learned after testing 42 research tools with my students:

The right tool at the wrong stage is useless.

Reading tools can't help you write.
Writing tools can't analyse your data.
Analysis tools can't make your presentations.

Most researchers pick one tool and force it to do everything.

That's why they stay stuck.

The productive researchers I know have a system:

→ Different tools for reading and understanding papers
→ Different tools for presenting research
→ Different tools for organising literature
→ Different tools for writing and editing
→ Different tools for data analysis

After years of testing, I've mapped the best 42 tools across 6 research phases.

Each one categorised by:
→ What it actually does best
→ Whether it's free or subscription
→ Which research stage it belongs to

Paper Reading. Literature Review. Paper Review. Data Analysis. Paper Writing. Research Presentation.

I've organised everything in the visual below.

Save it. You'll reference it more than you think.

---

Which research phase slows you down most?

#ResearchTools #PhDLife
Consensus Paperpal Bohrium Inkwell Gamma

I nearly failed a PhD student last year, as an examiner.
Not because her research was bad.
Because I couldn't follow her thesis.

67,000 words. Good range of findings. Three years of work.

But the structure was a mess.

Her literature review jumped between 40 different themes.

Her methodology appeared in three different chapters.

Her discussion repeated her findings instead of interpreting them.

I spent 6 hours trying to understand what she'd actually discovered.

That's when I realised something.

Most PhD failures aren't about bad research.

They're about bad structure.

After examining 50+ theses, I've seen the same pattern:
→ Brilliant students who bury their contribution in chapter 6
→ Strong findings hidden behind confusing methodology sections
→ Conclusions that introduce new ideas instead of landing the plane

Your examiner has 4 hours to read 80,000 words.

If they can't follow your story, they can't pass your thesis.

So I created a visual guide to the 7-chapter structure that works every time.

It's in the image below.

Save it. Print it. Refer back to it with every chapter you write.

Because your thesis isn't just proving expertise.

It's telling a story clearly enough that others can build on it.

----

Which chapter is giving you the most trouble right now?

#PhDThesis #AcademicWriting

4 fake citations. 3 hours wasted. 1 very frustrated supervisor.
My PhD student learned the hard way: ChatGPT isn't built for finding papers.

I watched a PhD student spend 3 hours on a literature review.

He used ChatGPT for everything.

Finding papers. Checking citations. Summarising findings.

The result? 4 hallucinated references and a frustrated supervisor.

The problem wasn't AI.

It was using the wrong tool for the job.

After testing 20+ AI tools with my research students, here's what actually works:

ResearchRabbit
Best for:
→ Discovering papers from seed articles
→ Visualising citation networks
→ Finding connected research you'd miss
→ Mapping a new field quickly

Semantic Scholar
Best for:
→ Finding highly cited papers
→ Tracking influential authors
→ Getting AI-generated summaries (TLDR)
→ Building reliable reference lists

Consensus
Best for:
→ Answering research questions with real studies
→ Evidence synthesis across papers
→ Checking what the literature actually says
→ Finding citations that won't disappear

Paperpal
Best for:
→ Academic writing and grammar
→ Journal-specific language suggestions
→ Improving clarity and flow
→ Polishing drafts before submission

The real advantage?

Knowing which tool to open before you start.

ResearchRabbit can't polish your writing.
Paperpal can't find connected citations.
Semantic Scholar can't synthesise evidence.
Consensus can't map an entire field.

Stop switching between 10 tabs hoping for the best.

Start matching the tool to the task.

I've mapped out exactly when to use each one in the visual below.

Save it. Share it with your lab group.

Which AI tool do you rely on most in your research right now?

#AIforResearch #AcademicTools

My first paper got rejected 3 times. Because I kept submitting to the wrong journals.
This how to find the perfect journal for your paper without wasting months on rejections

I'd pick based on prestige. Or what my supervisor suggested years ago. Or whatever came up first in a Google search.

Each rejection cost me 3-4 months.

By the time I figured out the pattern, I'd lost over a year.

That's when a colleague showed me journal matching tools.

I wish someone had shown me these on day one of my PhD.

There are 12 free tools that analyze your abstract and match it to journals where your research actually fits.

Major publishers like Elsevier, Springer Nature, Wiley, and Taylor & Francis all have them.

So do open access platforms like PLOS and MDPI.

And independent tools like JournalGuide and Scimago that let you compare across publishers.

The difference?

Instead of guessing and waiting months for rejection, you get data-driven matches in minutes.

I've listed all 12 tools in the visual below with links found in the comment too.

Use 2-3 of them to cross-reference results before submitting.

Your research deserves the right audience.

These tools help you find it.

---

What's your biggest frustration with journal selection?

#AcademicPublishing #PhDLife

Proposal development

Writing your upgrade proposal while working full-time is a different kind of hard.

Your supervisor is juggling 12+ students. They don't understand how it feels to squeeze proposal writing into exhausted evenings and weekends.

You get vague feedback like "needs more depth" with no clear direction.

Your upgrade deadline approaches. You start wondering if you'll even pass.

I've mentored 30+ mid to senior professionals through this exact struggle to successful completion.

20 years at a top 1% university. 40+ PhD examinations. I know where you're losing time.

I take on a small number of dedicated professionals for private premium 1:1 mentorship.

Interested? Start here: www.phdtoprof.com

Academic Writing

Writing your PhD while working full-time makes this ten times harder.

Your supervisor gives feedback like "needs better flow" with no clear direction.

You rewrite the same paragraph five times after a 10-hour workday.

You wonder if your English is good enough. If your arguments are strong enough. If you'll ever get published.

Frameworks and free guides help. But they can't give you personalised feedback on your specific writing.

I've mentored 30+ mid to senior professionals through this exact struggle to successful completion.

20 years at a top 1% university. 40+ PhD examinations. 130+ publications.

I know where your writing is losing marks. And I know how to fix it fast.

I take on a small number of dedicated professionals for private premium 1:1 mentorship.

Interested? Start here: https://forms.gle/L3wuDxfAgvDA17SD8

Abdel-Hameed Badawy

I almost quit my PhD in year 2. The isolation was crushing. 
Then I discovered academic podcasts. Suddenly, I had mentors in my earbuds.

People who understood the imposter syndrome.

The rejection letters.

The 3am writing sessions.

I wasn't alone anymore.

Although there were not back then as many podcasts as they are now.

That's why, I now curate them for my students.

So they never feel as alone as I did.

Here are 9 podcasts that have helped hundreds of my mentees survive (and thrive) in academia.

I've organised them by career stage:

For PhD Students:
→ The PhD Life Raft – practical survival strategies 
by Emma Brodzinski
→ PhD Talk – real solutions for everyday PhD problems
by Eva Lantsoght
→ Better Biologist – research skills and career development
by Kenan Kraković
→ The PhD Life Coach – support with PhD journey
Vikki Wright

For Early Career Researchers:
→ The Struggling Scientists Podcast – proof you're not alone
by Jayron Habibe, PhD and Suzanne Van Wouw
→ Beyond the Thesis With Papa PhD – career planning that works
David Mendes da Silva, PhD
→ Changing Academic Life – navigating academia's challenges
by Geraldine Fitzpatrick

For Academia to Industry Transition:
→ PostPhDirections – insider tips from hiring managers
Elena Hoffer, PhD  
→ PhD Career Stories – real stories of success and failure
by Tina Persson - Adaptability Intelligence, AQ


Turn your commute into a masterclass.

Your coffee break into a mentoring session.

Your workout into career development.

I've put all 9 with descriptions in the visual below.

Save it for when you need it.

---

Which podcast got YOU through your PhD journey?

#PhDLife #AcademicPodcasts

Helping Overwhelmed Doctoral Researchers| Specializing in Supporting Creatives with ADHD| Crafting Personalized Solutions for PhD Success and Work-life Balance| 1-to-1 coaching| Group Programmes| Institutional Packages

Vice Dean for Research at Universidad San Francisco de Quito & Associate Professor at Delft University of Technology

I help STEM students find and land their dream lab positions 🧬 Book an intro session below to see how we can work together.

Professional life coach at ThePhDLifeCoach.com

I share advice to help make your academic journey less of a struggle | Co-founder The Struggling Scientists | Communications Officer at Westerdijk Institute

Co-Founder The Struggling Scientists | Academic Development Coordinator |

Scientific & Medical Communications | Knowledge Mobilization & Research Impact | PhD | Health & Public Engagement | EN / FR / PT

Developing people and culture as a consultant, facilitator, trainer, speaker, podcaster, coach. Univ Professor i.R., TU Wien.

Executive, Leadership & Career Coach | Adaptability Intelligence | AQ | Innovation | Supporting people & teams and organisations in a fast-changing world driven by AI & technology

How to email potential PhD supervisors. The 6-step email system

Priya had a strong research proposal and excellent grades.

But her emails were long, generic, and focused entirely on herself.

Professors deleted them without reading past the first line.

That's when I taught her my 6-step email system.

Her next 10 emails got 8 responses.

Here's what changed everything:

Professors get 25+ emails weekly from students wanting PhD supervision.

Your email has 15 seconds to stand out.

Most applicants write emails like personal statements.

Formal. Lengthy. Self-focused.

That's why they get ignored.

Here's the system that transformed Priya's response rate:

1. Lead with relevance
Start with your strongest connection to their work. Not your life story.

2. Get to the point fast
Say what you want in the first two sentences. They're reading between meetings.

3. Show you know their work
Mention a specific paper or project. Prove you're not mass-emailing.

4. Explain your value
Don't just ask for supervision. Show what you bring to their research group.

5. Suggest a clear next step
Not "I hope to hear from you." Try "Would you have 15 minutes to discuss this?"

6. Make it scannable
Short paragraphs. White space. They might read it on their phone.

The results for Priya:

→ Response rate jumped from 4% to 80%
→ 4 supervisors agreed to discuss her proposal
→ 2 offered to support her scholarship application
→ She secured full funding at her first-choice university

The difference wasn't her qualifications.

It was making her emails impossible to ignore.

Most applicants write emails about what they want.

Smart applicants write emails about what they can contribute.

I've included a template with all 6 elements in the visual below.

Save it before your next outreach.

---

What's your biggest challenge when contacting potential supervisors?

#PhDLife #PhDScholarship

I've examined 47 PhD theses.
These phrases make me worry within 5 pages.
Here's how to fix them:

Every examiner has a mental checklist.

We don't talk about it. But we all have one.

And certain phrases trigger alarm bells before we've finished your introduction.

Here are 9 red flags that make examiners pause:

❌ "It is widely known that..."
What examiners think: Where's the citation? Are you avoiding the literature?
✅ Better: "Research has consistently shown (Author, Year)..."

❌ "This proves that..."
What examiners think: Statistical overreach. Do you understand your methods?
✅ Better: "These findings suggest..."

❌ "Obviously..." or "Clearly..."
What examiners think: If it's obvious, why are you doing a PhD on it?
✅ Better: "The evidence indicates..."

❌ "A lot of research shows..."
What examiners think: Vague. Which research? How much is "a lot"?
✅ Better: "Multiple studies (Author, Year; Author, Year) demonstrate..."

❌ "In conclusion, more research is needed."
What examiners think: Everyone writes this. What did YOU discover?
✅ Better: "These findings open specific questions about [concrete direction]..."

❌ "The researcher believes..."
What examiners think: This isn't a blog post. Where's your evidence?
✅ Better: "Based on these results, it appears..."

❌ "Perfect" / "Prove" / "Never" / "Always"
What examiners think: Absolutist language signals inexperience.
✅ Better: Use hedging words: may, could, suggests, indicates

❌ "Very unique" / "Extremely important"
What examiners think: These intensifiers weaken your argument, not strengthen it.
✅ Better: Let your evidence speak. Remove the adverb entirely.

The pattern?

Weak language signals weak thinking.

Even when your research is solid.

These phrases create doubt before you've had a chance to prove yourself.

Tools like Paperpal catch these patterns before submission.

→ Language Editing flags weak phrases automatically
→ Academic Paraphraser transforms vague writing into precise alternatives
→ Consistency Checks spot patterns that signal rushed work

I wish I'd had this when writing my own thesis.

Save this for your next chapter draft.

—

Repost and comment 'GUIDE' to receive my FREE "PhD Examiner Red Flag Phrase Guide: 50 Phrases to Avoid, And What to Write Instead" within 72 hours.

What phrase have you been told to remove from your thesis?

#PhDChat #AcademicWriting

Paperpal

How to read research papers 10x faster without losing your mind. I spent years doing it wrong. Then I found a method that cut my reading time by 70%.


Reading every word. Start to finish. Taking 3 hours per paper. Forgetting page 1 by page 15.

Sound familiar?

Then I found a method that cut my reading time by 70%.

It's called the Three-Pass Approach. Here's exactly how it works:

Pass 1: The Bird's Eye View (5-10 minutes)

Read only these parts:
→ Title, abstract, introduction
→ Section headings
→ Conclusions
→ Scan the references

That's it. You now know if this paper is worth your time.

Pass 2: The Content Grab (up to 45 minutes)

Now read with more care.
→ Study the figures and graphs carefully
→ Mark references you need to read later
→ Jot down key points in the margins

You can now explain this paper to someone else.

Pass 3: The Deep Dive (1-3 hours)

This is for papers you MUST understand fully.
→ Walk through the methodology step by step
→ Challenge every assumption
→ Identify hidden weaknesses

After this? You own that paper.

Here's the truth:

Most reviewers and readers only do ONE pass.

If they can't understand your paper in 5 minutes, they'll move on.

That's why your abstracts matter. Your headings matter. Your structure matters.

The three-pass method saves time. It builds understanding. And it makes you a better writer too.

I've used this approach for years. For conference reviews. For literature surveys. For background research.

It works.

Source: Keshav, S. (2007). "How to Read a Paper." ACM SIGCOMM Computer Communication Review, Volume 37, Number 3.

---

How many papers do you read per week? And do you have a system?

#PhDLife #AcademicTwitter

2 years for original research.
8 weeks for a systematic review.
One nearly broke me. The other launched my career.

Same journal. Same citation impact. Here's how to do it:

After my first 3 papers got rejected, a mentor asked me:

"Why are you making publishing so hard?"

I didn't understand the question.

Then she showed me her CV.

6 systematic reviews. All highly cited. Published in top journals.

She explained:
→ Systematic reviews synthesise what exists
→ They don't require new data collection
→ Journals love them because readers actually use them
→ And they get cited MORE than original research

My first systematic review took 4 months.

Accepted in 8 weeks. Now has 100+ citations.

That paper got me invited to editorial boards.

But here's what most people get wrong:

The methodology section makes or breaks your review.

Weak methodology = desk rejection.

After publishing multiple systematic reviews, I developed a 7-step framework:

1. Choose your Methodological Framework
PRISMA, Cochrane, or another established guideline.

2. Document your Search Strategy
List every database and your exact search terms.

3. Define your Inclusion Criteria
Specify populations, interventions, outcomes, and study designs.

4. Explain your Data Collection
Describe who extracted data and how you resolved disagreements.

5. Describe your Study Characteristics
Provide context on study sizes, locations, and methods.

6. Report your Quality Assessment
Name the bias tools used and how quality shaped your conclusions.

7. Detail your Data Extraction
Show your process so others can replicate it.

Miss any of these and reviewers will send it back.

I've broken down each step with real examples from published papers in the visual below.

Save it. Check your methodology against it before you submit.

---

Have you tried a systematic review yet? What's holding you back?

#SystematicReview #AcademicWriting

How do you turn 100+ papers into one coherent argument? I had no idea. 
Then I developed a 7-step system that changed everything.

"This is an incoherent mess."

My supervisor's words. About my literature review.

I had read 100+ papers over 6 months.

Notes scattered across 15 different documents.

But I couldn't write a single coherent paragraph.

I was drowning in information without direction.

That's when I developed my 7-step system.

It turned my chaos into my most cited publication.

Here's the framework:

1. Define Your Research Focus
Start with one clear question. Know exactly what's missing.

2. Search Systematically
Right databases. Clear search terms. Document everything.

3. Evaluate What You Find
Rate quality. Note strengths and weaknesses. Spot patterns.

4. Connect the Ideas
Group by theme. Map how concepts link. See the bigger picture.

5. Create Your Framework
Link theory to evidence. Build a logical argument flow.

6. Write and Refine
Draft from your outline. Get feedback. Polish ruthlessly.

7. Share Your Work
Present at conferences. Submit to journals. Build connections.

The results:

→ My literature review became a standalone publication
→ 47 citations in the first year
→ Two international collaborations started from it
→ It became the foundation for my entire PhD

The difference wasn't reading more papers.

It was having a system to organise what I read.

Most PhD students collect information without a plan.

Smart students build knowledge systematically.

I've broken down each step in detail in the visual below.

Save it before your next literature review.

---

Which step feels most challenging for you right now?

#LiteratureReview #PhDLife

3 patterns of misuse of AI in research I see every week that terrify me:

1. Researchers uploading confidential interview transcripts to ChatGPT

2. PhD students submitting AI-generated text without checking citations

3. Supervisors who have no idea what tools their students are using

Each of these can end a career.

I've seen researchers make the same mistakes over and over:

→ Uploading participant transcripts to ChatGPT (career-ending privacy violation)
→ Trusting AI-generated citations without checking (instant credibility destruction)
→ Feeding reviewer comments into AI (confidentiality breach)
→ Submitting to journals that ban AI entirely (automatic rejection)

The problem isn't AI itself. 

It isn't that researchers are using AI.

It's that nobody gave them the rulebook.
It's that nobody taught researchers the rules.

Universities don't cover this. Supervisors don't know it. Ethics boards are still catching up.

So after advising 500+ researchers, I created 13 golden rules for using AI ethically in research.

I've put them all in the visual below.

Screenshot it. Print it. Share it with your lab group.

Because what's acceptable today might be a retraction tomorrow.

---

Which of these 3 patterns have you witnessed?

#AIinResearch #AcademicIntegrity

Wrong PhD supervisor = dropped out within 2 years.
Right supervisor = completed while working full-time.
Here's how to choose well...

I've seen this pattern hundreds of times.

The supervisor you choose matters more than the university name on your certificate.

Here's what most working professionals get wrong:

They chase the famous professor.

Big name. Long publication list. Impressive CV.

But famous professors are busy. They travel. They have 20 other students.

They don't have time for someone who can only meet on Tuesday evenings.

Here's how to find the right supervisor instead:

1. Ask about flexibility first
Not publications. Not h-index. Flexibility.
"How do you work with students who have full-time jobs?"
If they hesitate, that's your answer.

2. Check their response time
Send them an email. See how long they take to reply.
If it takes 3 weeks now, imagine waiting 3 weeks for feedback on your draft.

3. Ask their current students
Not the ones who finished. The ones still struggling through.
"Does your supervisor understand when work gets busy?"
Their answer tells you everything.

4. Look for kindness over celebrity
A supportive generalist will get you to completion.
An unsupportive expert will get you to withdrawal.

5. Trust your gut in the first meeting
Do they ask about your life? Your job? Your constraints?
Or do they only talk about their research agenda?
You need a partner, not a boss.

Red flags to watch for:
"I expect you in the lab every day"
"Part-time PhDs never finish"
"I don't do video calls"

These aren't bad supervisors. They're just wrong for you.

The right supervisor exists.

You just need to ask the right questions before you commit.

What's the ONE question you'd ask a potential supervisor?

#PhDLife #AcademicTwitter

I used to spend 60+ hours searching for research gaps. Now I do it in under 60 minutes. Here's the free AI tool that changed everything.

Last year, every new project started the same way:

47 open tabs.
12 half-read papers.
Zero clarity.

Then a colleague showed me AllSci Corp.

It maps 20+ million research papers into hypotheses and evidence.

You don't just see what exists.

You see what's missing.

Last month I typed in my research topic.

Within 15 minutes I spotted a connection between two fields nobody had explored.

That gap became my latest paper.

The tool does 4 things brilliantly:
→ Organises results by hypothesis, not just keywords
→ Shows supporting evidence for each claim
→ Identifies the leading authors you should be reading
→ Visualises the entire research landscape so you spot gaps others miss

Here's how to use it in 4 simple steps:

Step 1: Enter your research topic
Type your question into the search bar and select "Detailed Search" for AI-powered discovery.

Step 2: Review hypothesis-backed results
Get results organised by hypothesis and evidence. Skip the noise. Go straight to verified claims.

Step 3: Explore hypotheses and key authors
Dive deeper into specific hypotheses. Identify the leading researchers you should be reading.

Step 4: Visualise the research landscape
Explore trends, journals, and connections. Use knowledge graphs to spot gaps nobody else sees.

I've mapped out each step with screenshots in the visual below.

The best part? It's completely free for researchers.

---

What research gap are you currently struggling to define?

#ResearchTools #PhDLife

AllSci Corp.

Your keyword search is lying to you.
It's hiding 40% of your literature.
Here's how to catch it

I've examined 47 PhD theses.
The same problem appears in almost every one.
Gaps in the literature review the student didn't know existed.

Not because they were lazy. Because keyword search failed them.

These questions consistently reveal gaps:

"Why haven't you cited the [adjacent field] literature?"
"This has been studied extensively in [discipline]. Why no mention?"
"How do you know you haven't missed something important?"

Most students can't answer the last one.

Why? The concept stays the same. The words change.

"Primary care" in the UK. "Family medicine" in the US. "General practice" in Europe.

Same system. Different terminology. Invisible walls.

My estimate: 40% of relevant papers get missed because of terminology barriers.

That's not sloppy research. That's a structural problem.

Here's the 5-step fix I share with every researcher I mentor:

1. Question your keywords: What would another field call this?
2. Search in sentences: Let semantic search find the right terms.
3. Follow citations: One good paper reveals terminology you didn't know.
4. Get outside eyes: A colleague in a related field spots blind spots.
5. Test before submitting: Different phrasings, different results = gaps.

Tools like Consensus use semantic search to understand concepts, not just keywords.

Same research question. 4x the relevant literature.

But tools alone aren't enough. You need to use them responsibly.

I've created a free guide: "How to Find the Papers You Don't Know You're Missing Using AI Responsibly"

Repost and comment 'SEARCH' below and I'll send it within 72 hours.

What terminology barriers have you found in your field?

#PhDChat #AcademicWriting

Consensus

You should not have to upload the same research paper six times to six different AI tools. But that is exactly what most PhD students do every week.
Here is the fix.

Every AI tool wants you to start from scratch.

This is ridiculous. But it is fixable.

A colleague came to me last week completely frustrated.

She had uploaded the same 38 papers to three different AI platforms.

108 uploads for documents she already had saved.

When she switched from Claude to ChatGPT for a different task, she lost everything. All the context. All the connections. Gone.

Each platform holds your documents hostage inside its own walls.

Your knowledge becomes platform dependent.
Your workflow becomes fragmented.
Your time disappears into endless re-uploads.

I showed her awRAG.io

Here is what it does:

You import your Zotero (or Endnote or others) library once.
One click.
All your papers indexed.

Then you access them from ANY AI tool.

ChatGPT. Claude. Gemini. Perplexity.

A browser extension connects your entire library to whatever AI you are using.

No more re-uploads.
No more starting over.
No more lost context.

The search understands what you mean.

Type "that qualitative methods paper about healthcare from 2021" and it finds exactly what you need. With relevance scores. With the specific passages.

For your PhD this means:

Literature reviews that pull from everything you ever saved.

Methodology sections backed by papers you forgot you had.

Theoretical frameworks built on your entire collection.

And here is what matters for sensitive research:

Your data stays in the EU.

GDPR compliant.
No AI training on your documents.
SOC 2 Type II certified infrastructure.

Your thesis data is not feeding someone else's model.

I created a step-by-step visual showing how to set this up.

Takes 10 minutes.

The guide is below.

How many times did you re-upload the same paper to different AI tools this week?

#PhDLife #AcademicResearch

awRAG.io

I've examined 43 PhD students.
Only 12 had the training they actually needed.
Here's what nobody tells you about PhD programs:


The rest? Left to figure it out alone.

Here's what nobody tells you about PhD programs:

Universities charge $80K+ in fees.
They teach you theory.
They teach you research methods.
They teach you how to run experiments.

But they don't teach the skills that actually determine your career.

→ How to network strategically
→ How to navigate the hidden job market
→ How to write papers that get published
→ How to manage your supervisor relationship
→ How to position yourself for faculty or industry roles

I learned this the hard way.

My PhD program never mentioned career strategy.

I spent 2 years applying to jobs with no responses.

No one told me 70% of PhDs struggle with the same thing.

No one told me only 8% land faculty positions.

The gap between PhD training and career reality is massive.

So what do successful PhDs learn outside the curriculum?

5 skills top students develop on their own:

1. Strategic publishing (quality over quantity)
2. Building a research identity before graduating
3. Conference networking that leads to opportunities
4. Writing that connects with readers, not just reviewers
5. Managing up with supervisors who are too busy

These aren't taught in any module.

But they separate those who thrive from those who struggle.

I made a promise when I became a professor:

I would teach what I wished someone had taught me.

The system isn't broken by accident.

It's designed for research output, not researcher success.

But you don't have to wait for programs to change.

Start building these skills now.

What skill do you wish your PhD program taught you?

#PhDLife #AcademicCareer

----
Sources:

Hazell, C. M., Niven, J. E., Chapman, L., Roberts, P. E., Cartwright-Hatton, S., Valeix, S., & Berry, C. (2021). Nationwide assessment of the mental health of UK Doctoral Researchers. Humanities and Social Sciences Communications, 8, Article 305. https://lnkd.in/dr6PzSmK

The mental health of PhD researchers demands urgent attention. (2019). Nature, 575(7782), 257-258. https://lnkd.in/du9HcyAF

Larson, R. C., Ghaffarzadegan, N., & Xue, Y. (2014). Too many PhD graduates or too few academic job openings: The basic reproductive number R₀ in academia. Systems Research and Behavioral Science, 31(6), 745-750. https://lnkd.in/dyda-SKa

Evans, T. M., Bira, L., Gastelum, J. B., Weiss, L. T., & Vanderford, N. L. (2018). Evidence for a mental health crisis in graduate education. Nature Biotechnology, 36(3), 282-284. https://lnkd.in/dtrJCzsF

A PhD student in our programme almost submitted a paper with 3 fake citations. They looked perfect.
5 AI Hallucination Red Flags & How to Spot Them:

ChatGPT had generated them. 

Author names. Journal titles. Even DOIs.

None of them existed.

Her supervisor caught them the night before submission.

This is why universities are panicking about AI in research.

And why I now run workshops for institutions on responsible AI use.

Here's what every researcher needs to know:

The 5 AI Hallucination Red Flags:

1. Citations you've never seen before
AI loves inventing plausible-sounding references. If you didn't find it yourself, verify it exists.

2. Statistics that seem too perfect
"Studies show 73.4% of researchers..." If it's suspiciously precise, it's probably fabricated.

3. Author names that don't appear on Google Scholar
Real academics have publication trails. Fake ones vanish when you search.

4. Journal names with slight misspellings
"Journal of Applied Neuroscience" vs "Journal of Applied Neurosciences" — one exists, one doesn't.

5. Claims that contradict your domain knowledge
You're the expert. If something feels wrong, it probably is.

The Verification Protocol I Teach in University Workshops:

Step 1: Never use AI citations directly
Step 2: Cross-reference every claim with primary sources
Step 3: Check every DOI link actually resolves to a real paper
Step 4: Document exactly how AI was used in your methods
Step 5: When uncertain, disclose more rather than less

One fake citation can end a career.

Five minutes of verification can save it.

---

What's the most surprising AI error you've caught in your research?

#AIinResearch #AcademicIntegrity

70% of researchers will use AI incorrectly this year.
Not because they're lazy.
Because nobody taught them the right way.

I've spent 15 years in academia. Made Professor by 40. Helped over 10,000 researchers navigate their careers.

And I've never seen a shift this fast.

AI is changing everything about how research gets done. 

The problem? Most researchers are using it to replace their thinking instead of support it.

That's a mistake that will catch up with them.

I joined Jeremy Bennett to break down exactly how to use AI ethically in research.

We covered:
→ Why AI should support process, not replace thinking 
→ How to manage research while working full-time 
→ The role mentors and structure play in finishing faster 
→ Why "sounding human" is becoming a competitive advantage 
→ How to choose a PhD topic you'll actually stick with

The researchers who get this right will pull ahead. The ones who don't will spend years rebuilding trust.

Have a listen. Link in Jeremy's post below.

What's your biggest question about using AI in your research?

Wondering how to use AI ethically in research?
 
Emmanuel Tsekleves shows you how.
 
In this episode, discover:
 
How to use AI in research the right way. 
The importance of building support systems.
How to manage your time while working full-time.
Why AI should support process, not replace thinking. 
How mentors and structure help you finish faster. 
Why passion matters when choosing a PhD topic. 
Why sounding human is starting to matter.
 
What’s your biggest 2026 goal?  
↳ Let us know in the comments.

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