Alma.Me

At Alma.Me, we help PhDs kick start their careers in industry through on-demand courses, online communities, networking, and resources to help them make the transition from academia to industry with confidence.

Co-Founder and CEO

Karolinska institutet

PhD candidate

Research Assistant

Founders Sunday

Founders Sunday serves as a non-profit educational platform and support for founders in all continents of the world (1300 + start-ups/scale-ups) 

The community meets up every Friday 1pm CET on zoom for lively discussions related to the founders journey (#founderscoffee☕️) 

For founders - by founders 💡

Manager

PhD Careers Beyond Academia Club at Karolinska Institutet

Organizer

Department of Immunology and Microbiology (ISIM), University of Copenhagen

Visiting PhD student 

Engel Apotheke

Pharmaceutical-technical assistant 

ratiopharm

Laboratory Technician

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

The world: PhDs are experts.

Reality: experts in managing chaos, solving impossible problems, communicating clearly, and Googling things very fast. (Yes… Googling is a skill.)

♻️ Share to help demystify what PhDs really bring to the table.

-------------
If you need support communicating your skills to non-academic employers, check out what we do at Alma.me - we’d love to help.

Happy Thursday 🥳

JSESSIONID

li_at

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

An academic CV  ≠ Industry Job 

If your CV is more than 2 pages, starts with Education, and lists Publications, Conferences, and Awards - and you keep hearing nothing back - this is why.

Industry hiring managers want a clear, focused resume that shows how you’ve used your skills to create impact.

Here’s what actually works 👇
✅ 1–2 pages max
✅ Professional Experience first, not Education 
✅ Skills and achievements, not publications
✅ Add a link to your papers instead of listing them
✅ Clean, one-column layout (no over-designed templates)

This is the CV format that landed our PhDs interviews at companies such as Sanofi, Apple, Fannie Mae, PayPal, and Duolingo.....

Get your free editable version. Download it via links in the comments👇

♻️  Share this with other PhDs 

Happy Wednesday 🙌

Resume template_PhD

If you're doing a PhD right now, the odds of building a long-term academic career are, unfortunately, stacked against you.

The truth is harsh: 
Only  4-5 % of PhDs will stay in academia long-term, and for many PhDs the future about their next career step feels uncertain
 
And this isn’t just a feeling. 
A Nature Magazine career survey showed that more than half of PhD students worry about their career path, and nearly half fear there aren’t enough research jobs. Years later, nothing has changed. The path after academic is still unpredictable and fragile for most. 

Leaving academia can feel like stepping into the unknown - like being pushed out of the only environment you’ve ever belonged to. It’s scary because for years, the path was laid out for you. 

Now suddenly… you’re supposed to navigate a new world without a map. 
But you don’t have to do it blindly. 

I put together a free 10-step guide to help you make that transition with confidence - the exact framework we use in our job accelerator program to help PhDs land roles at Sanofi, Fannie Mae, Siemens Healthineers, Shield Legal and more.

If you want stability, clarity, and a plan you can actually follow, this guide is your first step. 

You’re not alone in this. 
And you don’t have to figure it out in the dark. 

Download the guide to get an idea about how to approch the fist step into industry: https://lnkd.in/dwD-7nJ4

♻️  Share to help a friend 

Happy Monday 🥳

(4) Feed | LinkedIn

Today I got something fun in the mail - a Nature Magazine issue with an article I was interviewed for along other scientist: 'Scientist who have cracked LinkedIn'

Big thank you to Anne Marie Conlon for sending it over and writing such a wonderful piece! 

Holding it made me smile a little because… I actually started using LinkedIn during my PhD in 2022, at a time when absolutely no one around me was doing it. 

Back then, LinkedIn in my lab basically meant: 
 – a profile photo from 2014 
 – two connections  
 – a spares profile with some skills 

So yes - posting felt a bit uncomfortable simply because it wasn’t “a thing” scientists did. 

But it was a place where I could meet people who I would never meet inside academia: founders, PhDs talking about careers, PhDs creator who talked about other things related to the PhD journey…  
 
It became a small corner of the internet where I could talk about something I deeply cared about: PhD careers, and the messy, confusing, exciting process of figuring out what comes next

And honestly? 
Half the time I had no idea what I was doing but I loved writing and sharing content - so I kept going because I loved connecting with people who were also questioning, exploring, building. 

So seeing this Nature article today felt strangely full-circle. 
Not because “I cracked LinkedIn”.

But because it shows that scientists can show up in new spaces, start conversations, and build real networks beyond the lab. 

 If you're a PhD thinking "should I even be on LinkedIn?" -here's my honest tip (and I recommend reading the tips of the other scientist in the article -tons to learn from them)

Just spend 10 minutes a day and keep it simple stupid at this stage to see how it developed fro you: 
- Read one thing 
- Engage with some people through the comments this builds trust and network 
- Follow people who inspire you 
-  Post something small when you feel like it 

That’s it. 
No real strategy. 
No perfection. 
No “brand voice.” 
Just you being human. 

Happy Monday 💙

Dear PhDs - You are employable beyond academia.

You don’t need to become someone else to fit in industry. 
You don't need to become more of an expert - you are an expert.

You just need to learn how to translate the skills you got in industry relevant language.

You are not starting over -you are evolving.

♻️  Share with to help a friend

Dear PhDs - You're not starting from zero when moving into industry 

You’re starting from experience.  Years of research, problem-solving, teaching, writing, mentoring -  that all counts. 

You don't need to up-skill. You don't need to learn more. 

You need to learn to speak the language of industry.

Happy Sunday 💙

Dear PhDs - You’re not behind in life. 

You’ve spent years mastering critical thinking, independence, and resilience. 

You didn’t take a detour - you built depth and broadened your horizon. 

Now it’s about learning how to show it differently. 

Thank you for doing the hard work. 

Happy Sunday 💙

When I moved from academia into entrepreneurship, it wasn’t a single decision.
It was a process.

A long one - confusing, exciting, messy, and full of testing.

It actually started two years before I even graduated.
I didn’t wake up one day thinking, “I’ll be a founder.”

I simply followed the small signals:
- I took two entrepreneurship courses during my PhD.
-  I joined different organizations just to see what was out there.
- I met people completely outside my academic bubble.

And slowly, something clicked.
During that time, I realized I was naturally drawn to the topic of careers.
I started organizing career sessions for other PhDs - and it just felt right.

I’m a gut-decision person. I need to feel things.
And that feeling was unmistakable:
This is my thing.

I spoke with many of PhDs who transitioned into industry.

I learnt from each of them about things I want and don't want in a career.

But the more I talked to people, the more I realized:
Why build someone else’s dream when I could build my own?

So I made a decision:
I’m going to make this happen.
I talked to people who built companies.
I connected via LinkedIn with other founders.
I learned from every conversation.

And then something magical happened:
I met Angela Priest — my co-founder of Alma.Me — who lives in Denver, Colorado. What are the odds that we would ever meet in real life?

But here we are, building a company that changes PhDs’ lives.

And here’s the thing:
If you have a dream to move into industry after your PhD or Postdoc and don’t want to do this alone…

If you want a proven strategy that has helped PhDs land roles at Sanofi, PayPal, Fannie Mae, and so much more…

Then now is a very good moment.
Because until November 30th at 11:59 PM MST, we’re offering 26% off the initiation fee of our Job Accelerator Program ( you can start the program until the 26th of June).

Because we want more PhDs to transition with clarity instead of confusion.
With a roadmap instead of guessing.
With support instead of doing it alone.

👉 Apply to our Job Accelerator Program and book your intro call before 30th of November  11:59PM MST: Link in the comments 

You don’t need to figure this out by yourself 🙌

As a PhD, you’ve gained valuable skills.

You’ve learned to thrive in ambiguity, handle complexity, and approach problems analytically.

But none of this is seen by hiring manger if your resume doesn’t translate your value into industry language.

If you’ve ever thought:
 ❌ “Why am I getting no responses?”
 ❌ “I’ve made 20 revisions — what am I missing?”
 ❌ “How do I know what a hiring manager values?”

Then you need this:
🔴 Live Resume Review (Dec 2nd — 6 PM CET / 10 AM MST)
A real-time breakdown of a PhD resume from our Alma.Me community — reviewed by someone who has been on the other side of the hiring table for two decades.

Angela Priest (my co-founder) has:
 • 20+ years hiring across startups → big companies → tech → insurance
 • Built entire hiring processes and high-performing teams
 • Created for the PhDs in our job accelerator program a resumes that landed interviews at Amazon, Apple, Sanofi, Fannie Mae, Duolingo, and more

In 60 minutes, you’ll see:
 👉 Why your resume may not be getting responses
 👉 What hiring managers instantly notice
 👉 The 3 sections that usually need a complete rethink
 👉 How PhDs accidentally hide their strongest skills
 👉 How to communicate impact (not tasks!) in a way industry immediately understands

If you want clarity on what’s holding you back — you’ll get it here.

Join via the QR in the event image, or via the link in the comments.

And save the date:
Dec 17th — Live Mock Interview Session.

Because your transition deserves clarity, not guesswork 🙌 

♻️ Share to help other PhDs

Happy Tuesday 🥳

Wow - yesterday more than 220 PhDs joined our live resume review session.

Researchers from every corner of the world showed up, all with the same question:

“How do I turn my long academic CV into a strong industry resume?”

If you’ve ever stared at a job ad and thought “I have no idea how to present myself for this…” — this session was built for you.

Here’s what we covered:

✅ How to overcome academic bias in hiring — yes, it’s real
✅ The formula for a compelling professional summary
✅ How PhDs can translate research into industry-ready skills
✅ How to write impact-driven bullet points (What → How → Result)
✅ How to showcase publications, grants, and conferences without overwhelming your resume
 … and so much more.

If you missed it and want to rewatch the full session, it’s now on my YouTube channel.
 👉 https://lnkd.in/dArdRgXM

Next up: A live mock interview - December 17th

Most PhDs never get real feedback after an interview — just a generic “we’ve decided to move forward with someone else.” And that leaves you guessing.

When we work with PhDs in our program who’ve been through this, they often have true “wow” moments during mock interviews with us.

For the first time, they finally understand the actual reasons they didn’t move forward - and more importantly, how to fix them.

If interviews make you freeze, over-explain, or feel like you have to “pretend” to be the expert… this mock interview session will change everything.

Angela will run a real industry-style interview.

🎟️ Register here: https://lnkd.in/djGT7Wb9

Happy Wednesday 🙌

Most PhDs spend hours tailoring a resume…

Only to end up feeling unsure, overwhelmed, and still not confident they’re doing it “right.”

Inside our job accelerator program, we teach a system that takes less than 10 minutes - and it works because it’s based on how hiring managers (like my co-founder Angela) actually evaluate resumes.

Here’s the 5-step method our PhDs use to tailor their industry resume quickly and effectively 👇 

1. Research the Role
Look at 5–10 recent job postings for the same title.
Patterns only appear when you look across multiple ads - not one.

2. Identify Themes
Across those postings, pull out:
 • 6–7 common responsibilities
 • 3–4 repeated qualifications
 These become your resume’s “anchor points.”

3. Find the KPIs
How does industry measure success in this role?
Number of users? Timelines? Revenue? Efficiency?
These KPIs show you how to quantify your accomplishments.

4. Create a Template
Build one strong base version of your resume for that role. Then:
 • match your experiences to the themes
 • quantify using the KPIs
 This is where your academic work becomes industry-relevant.

5. Tailor Your Application
Tweak keywords → apply → done.
 Because when your template is strong, tailoring takes minutes.

Most PhDs were never taught this - and that’s exactly why it feels so hard.
But once you learn the system, everything clicks.

📌 Download your printable cheat sheet here for later : https://lnkd.in/gPXWAFUp

You don’t need more time.
You need a process — and our cheat sheet has teaches you exactly that

♻️  Share this to help other PhDs

The hidden curriculum of every PhD.
(Featuring: cleaning floors, stacking pipette tips, and solving problems no one warned you about 😂)

Thank you for the fun collaboration, Raul Peña.
Your PhD skills can take you anywhere - but somehow they also had you doing everything:

🧠 The intellectual stuff:
-designing experiments from scratch
-analysing complex data and turning chaos into clarity
-communicating science to any audience
-managing long-term projects with shifting timelines
-learning new tools and methods overnight
-thinking critically under pressure

🤡 And then the other stuff every PhD knows too well:

-refilling 70% ethanol bottles… over and over…sometimes even making it)
-pushing a cart of empty 50 ml tubes like you’re restocking a supermarket aisle
-hunting for missing reagents that somehow walked away
-fixing lab equipment with tape, hope, and YouTube tutorials
-reorganizing the −80°C freezer because no one respects labels
-collecting biohazard waste bags and dragging them down the hall
-defrosting freezers like you’re leading a polar expedition
-labeling tubes until your handwriting becomes its own scientific font

This blend - the intellectual + the absurd - is your real superpower in industry.
Because you can think deeply and get things done, no matter what chaos shows up. 

If you are doing a PhD or Postdoc - Don't forget you are amazing 🙌 

What am I missing?

♻️  Repost to make another PhD feel seen.

Happy Wednesday 🥳

She did it after her PhD - despite hearing that no one had ever done it before.

Kertu Tenso, PhD transitioned into data science after her PhD in global health - and she did it by being intentional, proactive, and incredibly strategic.

In this episode, we talk about how early clarity became her superpower:
🔹 She started exploring data science in her first year of her PhD
🔹 Checked job listings to understand what skills she’d need
🔹 Took extra math, stats, ML and Python courses
🔹 Built machine learning directly into her dissertation
🔹 Kertu shares many valuable tips how you can make that transition too

What stood out to me most is how she built the career she wanted while still doing her PhD, even when others told her it wasn’t possible.

Her story shows the power of knowing what’s next: when you have clarity, you can shape your PhD intentionally, develop applied skills, and create opportunities that align with your future - not just your present.

🎙️ If you're considering a transition into data science (or any industry role), this episode is a must-listen. It's so super inspiring - don't miss out on it. 

👉 Tune in to the full conversation here: https://lnkd.in/dw2a4W-D

Happy Tuesday 💙

It’s Thanksgiving today — and while we don’t typically celebrate it here in Europe, having an American co-founder means I get to borrow the tradition.
So here comes a gratitude post. ❤️

🙏 I’m deeply grateful for the impact we’ve made this year.
This month alone, five PhDs landed industry jobs through our program.
 Five people who some...
 ➡️ had been trying for months and felt their confidence slipping
 ➡️ were running out of money and needed stability now
 ➡️ didn’t want to go through this transition alone
 ➡️ needed structure, direction, and someone who genuinely understands their journey

Each story reminds me why Angela and I built Alma.Me - not just to help PhDs get jobs, but to help them rebuild confidence, self-worth, and clarity.

🙏 I’m grateful for our team.
Michael Orndoff - you believed in us from day one. We couldn’t be more grateful.

Jevin Lortie, Ph.D. & Emily Cohen, PhD - you are extraordinary coaches and human beings. I’m so glad we get to learn and grow together.

Sofija Sundmann & Chiara Tremolanti - thank you for jumping in headfirst. Startups can be messy, but the impact you’ve already made is huge.

🙏 And of course… Angela Priest.
My co-founder, friend, and business partner.
With 20+ years of hiring experience, she understands industry hiring like few do.
 
Together, we bridge what PhDs need most: real academic understanding + real hiring expertise.

💛 Giving back to the PhD community
We know that finances can be a real barrier for many PhDs who need support in their transition.

 So tomorrow, we’re doing something special.
👉 From tomorrow on, we’re offering 26% off the initiation fee for our Job Accelerator Program.

 If you want to know more, stay tuned.

Start 2026 knowing you don’t have to navigate your job search alone - and that you’re supported every step of the way.

🧡 Happy Thanksgiving to our American friends around the world.
And thank you to every PhD, postdoc, and professor who trusts us with their career journey.

We see you. We believe in you. And we’re here for you.

She finished her PhD in computational neuroscience and just accepted her first industry role as a Medical Writer — all in 41 days.

🔹 44 applications
🔹 2 interview rounds
🔹 1 offer she was excited about

What we worked on together:
 ✅ We rebuilt her resume from scratch - industry-ready, skills-forward, no academic jargon
 ✅ We coached her through interviews - how to be conversational, confident and clear

Why she succeeded (and what other PhDs can learn):
 1️⃣ She followed our process / protocol - no overthinking, just implementing.
 2️⃣ She was authentically herself in interviews - She gave concise, thoughtful answers, stayed human, and let her personality come through.
 3️⃣ She showcased her skills, not job titles - Even though she had never worked as a medical writer, she clearly communicated that she understood what this role was about and how she can contribute
 4️⃣ She didn’t chase perfection or feared mistakes - she trusted her instincts in interviews- after all it is a learning process

If you want to accelerate your job search, you can apply to our Job Accelerator Program here: https://www.alma.me/

Happy Friday 🥳

Most PhDs never get real feedback after an interview — just a generic
 “we’ve decided to move forward with someone else.”

That leaves you guessing:
Was it my answer?
My experience?
My “fit”?

When we work with PhDs who’ve been through this, they often have true “wow” moments during our mock interviews. 
For the first time, they finally understand the actual reasons they didn’t move forward - and, even more importantly, how to fix them.

When we run mock interviews with PhDs in our program, they often have real “wow” moments because, for the first time, they understand why they didn’t move forward - and how to fix it.

If interviews make you freeze, over-explain, or feel like you have to “pretend” to be the expert… this session is for you.

The top 3 interview struggles we see again and again:
- Rambling or giving overly long answers because you’re unsure what the interviewer really wants
- Being too stiff or formal instead of sounding like someone they’d genuinely want to work with
- Going too technical when the hiring manager actually wants clarity, not complexity

In this live mock interview, you’ll learn exactly how to turn these challenges into strengths - with practical strategies you can use immediately.

Live Mock Interview – PhD-to-Industry Ready Series
December 17th, 6 PM CET / 10 AM MST
Led by Angela Priest, hiring manager with 20+ years of experience who has helped our PhDs land jobs at Sanofi, Siemenes Healthineers, Fannie Mai, etc. 

Secure your spot via QR code or link in the comments 👇

Share to help a friend ♻️

Self-rejection limited her job opportunities.

I recently met with one of our PhDs who was feeling discouraged because her application rate had dropped.

When I asked why, she said:
“I just don’t see many positions I’m a good fit for.”

We went through a few openings together. Some made sense - not the right match.

But then we found one that fit her perfectly… every skill, every qualification - except one line.

“Must know how to operate machine X from company Y.”
She’d used the exact same type of machine - just from company A.
And she didn’t apply.

I encouraged her to go for it.
If you can master one version, you can learn another.

And that’s the thing - I see this all the time.

PhDs, postdocs, even tenured professors often look for a 100 % match before applying.
 But you’re not supposed to tick every box - you’re supposed to have room to grow.

👉 In our Job Accelerator, we work on this exact mindset shift — translating academic experience into language that shows industry readiness (even when you don’t meet every requirement).

If you’ve been holding back because you’re not “perfectly qualified,” join our job accelerator program: Apply here: https://www.alma.me/

Happy Monday 🥳

Let’s normalize a few things about the job search for PhDs. 

These are things I see every day with the PhDs in our program - and if any of them are happening to you, it's not you. 

Please don’t start questioning your value. 
✅ Yes, interview processes can move very slowly - sometimes 3+ months. 
✅ Yes, some companies have 4+ rounds of interviews. 
✅ Yes, some will ghost you completely. 
✅ Yes, it can take sometimes weeks before you hear back about next steps. 
✅ And yes - some PhDs get invited to interview more than 4 weeks  after applying. 

If these things are happening to you, you're not alone. 

The job search in industry isn’t a reflection of your worth - it’s a process that takes strategy, patience, and perspective. 

👉 If you’re tired of navigating it on your own and don't want to do it alone anymore join our job accelerator program 

We’ll help you build a clear strategy, keep your confidence high, and finally move through the process with support - not self-doubt. 

Apply here: https://www.alma.me/

Happy Tuesday 🌻

I just got back from speaking at Postdoc Day in Portugal - and being in that room reminded me exactly why I do this work.

A huge thank you to the Postdoc Union GIMM for the invitation and for creating such a thoughtful space for postdocs to explore their next steps.
It was an honour to be part of it.

Every time I talk to postdocs, many of the same things come up.

And if more PhDs knew them earlier, their career transition would feel a lot less overwhelming.

1️⃣ Your publications aren’t your greatest asset - your skills are.
Industry hires for what you can do, not what you’ve published.
You already use valuable skills every day - you just haven’t been taught to translate them.

2️⃣ Industry doesn’t hire the “most qualified” - it hires the best fit.
Recruiters skim your CV in seconds.
Hiring managers want someone curious, collaborative, and human - it's more than skills.

3️⃣ Impact beats description. Always.
“Conducted research…” doesn’t stand out.
“Improved, enabled, led, accelerated…” does.
Show what changed because of your work.

Portugal was a beautiful reminder:
Postdocs are far more prepared for industry than they think - they just need the right tools and language.

Thank you for making career development a priority: Miguel M. Santos, Tomás Gomes, Franziska Hildebrandt, PhD, Catarina Rosa, Christian Gnann, and David Anaguano from the PostDoc Union GIMM. 
Great job 🙌 

Hope to see you soon again beautiful Portugal 💙

“Should I just wait until next year to start your Job Accelerator Program?”
It seems to make sense at first - but the short answer is no.
Here’s why:

1️⃣ If you start thinking about getting your application ready in January, you’re already behind.

The biggest hiring wave of the year happens right at the start of January.

By starting now, you enter the new year with:
-an industry-ready resume aligned with employer needs
-a clear understanding of which roles you’re qualified for
-a job search strategy that gets you seen by employers and hiring managers
- momentum - not confusion - when hiring season opens
This positions you to compete immediately when January roles go live.

2️⃣ We are offering a Black Friday discount of 26% off the initiation fee.
This offer is only available until Sunday. the 31st of November 11:59PM MST.
Here’s what you need to do:
 ✔️ Apply + book your intro call before the deadline on Sunday
 ✔️ The call itself can take place later
 ✔️ If you qualify for the program, the discount applies

Simple and straightforward. 

Not sure if you're a fit?

Here are examples of PhDs we helped transition into industry roles:
-PhD in Economics → Quantitative Modeler at Fannie Mae
-PhD in Immunology → Scientist at Sanofi
-Postdoc in Psychology → Senior Decision Scientist at PayPal
-Tenured Professor in Theoretical Mathematics → Senior Advanced Analytics Analyst at Grainger
-PhD in Computational Neuroscience → Data Scientist I at Scribd

or reach out if you have questions.

If you want 2026 to be the year you transition into industry, the right time to start and invest in yourself is now - not in January.

📌 Apply and book your intro call before Sunday to secure the 26% Black Friday discount:

👉 Link to apply in the comments 

Happy Black Friday 🙌

🩺I take researchers from goals to published results 🇮🇳 🇬🇧 Founder II Academic Writing Mentor || AI researcher || Homeopath ✅️Need Research Solutions❓️ Go to my ABOUT section.🔻

I specialize in testing AI tools for literature reviews, academic writing, editing and statistical analysis, sharing insights that enhance research productivity and workflow.

As a PhD in Life Sciences, I am passionate about guiding academics and PhDs from research concept to completion, ensuring they have the right tools, methodologies and mentorship to succeed.

🎯 How I Help Researchers & PhDs??

Through 

🟪 RESEARCH MADE CLEAR 🟪

I offer consultancy services in:

✅ Scientific Writing & Editing: Ensuring clarity, coherence and impact in research papers.
✅ PhD Mentorship & Research Methodology: Supporting scholars in thesis writing, research design, and proposal development.
✅ Data & Statistical Analysis: Providing expertise in biostatistics, data analysis and result interpretation.
✅ Faculty & Student Development: Training in AI-powered research tools & ethical considerations.
✅️ Webinars & Workshops: How to use AI tools for Literature Review, research writing and Research Management, ethically.

🔍 My Experience & Research Contributions:

With 10+ years of experience across multidisciplinary research projects, I have:
📌 Led & coordinated multiple research trials and longitudinal surveys as a Research Manager.
📌 Published 8+ peer-reviewed papers in evidence-based medical writing.
📌 Developed the MAPNI questionnaire—a validated tool assessing perceived stigma towards mental illness in India.
📌 Taught Research Methodology & Biostatistics as an 'Assistant Professor', mentoring 500+ academic professionals in thesis & dissertation writing.
📌 Supervised successful scholarship applications for the Short-Term Studentship in Homoeopathy (STSH, CCRH, India).

📢 Let’s Connect
✅️Need expert guidance in research writing, AI tools or statistical analysis?
✅️Looking for collaborations, training sessions or mentorship?

💌 Email: dps@researchmadeclear.com
📩 DM me here on LinkedIn!

Dr Priya Singh PhD💜MD (Hom.)

❓Are you still doing every part of your research manually, when AI can do half the heavy lifting?

Between managing references, digging through papers, writing drafts and presenting findings 

It often feels like we’re juggling ten different jobs.
 
However, AI can make your research journey much smoother if you know where to look.

That’s exactly why I curated this list of Top 30 AI Tools for researchers

From finding literature and identifying research gaps to writing, editing and visualizing data, these tools save time, boost productivity and help you stay focused:

1. Literature Review:
ResearchRabbit: https://lnkd.in/eZ4PMRup
ResearchPal: https://lnkd.in/e_nPmJTK
Litmaps: https://www.litmaps.com/
Liner: https://lnkd.in/epvViufW (get 40% off)

2. Data Extraction:
SciSpace: https://lnkd.in/ehbWNQdr (PRIYA40, PRIYA20)
Covidence.org: https://www.covidence.org/
Elicit: https://elicit.com/

3. Note taking:
Notebook LM: https://notebooklm.google/
DocChat: https://docchat.iferp.in/
Microsoft One Note

4. Research Gap:
Scite: https://scite.ai/
AnswerThis (YC F25): https://answerthis.io/
Consensus: https://consensus.app/

5. Writing & Editing:
Paperpal: https://lnkd.in/eWjg4UKk (PAP20)
ProWritingAid: https://prowritingaid.com/
Jenni AI: https://jenni.ai/
Trinka.ai: https://www.trinka.ai/

6. Data Visualisation:
R studio
Julius AI: https://julius.ai/
Tableau: https://www.tableau.com/
Flourish: https://flourish.studio/

7. Reference Management:
Zotero: https://www.zotero.org/ 
Mendeley: https://lnkd.in/efjwZPhC
EndNote: https://lnkd.in/ebG2a5zG

8. Presentation:
Gamma: https://gamma.com.ai/
Microsoft copilot for PowerPoint
Simplified 

9. Research Management:
Otio: https://otio.ai/
Notion:  
ClickUp 

📌 Remember: You don’t need all 30 tools.
 
Pick 1 or 2 from each category to match your current research stage and build from there.

Let AI support your research, not stress it.

You’ll be amazed how much time and mental energy you save.
 
Repost to help fellow PhDs, MPhils, and early-career researchers build their research toolbox.

PS: What tools would you add to this list?
Share in the comments.

Most PhDs overcomplicate qualitative research.

I suggest my mentees to follow these guidelines for doing strong qualitative research:

1. Start with a focused question, not a vague topic

 Bad: “I want to explore leadership.”
 Better: “How do first-time managers in X context make decisions under pressure?”

The clearer your question, the easier every next step becomes (interview guide, coding, themes).

2. Talk to the right people, not just the available ones
 
Your sample should be:
Directly connected to your research question
Able and willing to share experiences
 
Don’t just recruit whoever says yes. Be intentional.

3. Design interviews like a conversation, not an interrogation

Use:
Warm-up questions (“Tell me a bit about your role…”)
Open questions (“Can you walk me through…”)
Gentle probes (“Can you tell me more about that?”)
 
Your goal is to help participants tell stories, not give one-word answers.

4. Record your decisions as you go
 
Keep a simple research diary:
Why you changed a question
Why you added/dropped a code
What surprised you in the data

 This becomes gold later when you write methods, reflexivity, and limitations.

5. Transcription: good enough > perfect

Capture:
What was said
Key emotions (laughs, long pause, sighs) when they change meaning
 
Perfectionism in transcription can drain your energy before the real analysis starts.

6. Coding isn’t about “finding the right answer”
 
Think of coding as labeling pieces of meaning:
First round: messy, descriptive labels (what is being said?)
Later rounds: more focused (what does this mean in relation to my question?)

 You’re moving from labels → patterns → themes.

7. Your themes must answer your research question
 
A theme is not just a topic like “communication” or “stress”.
 A strong theme sounds like an insight:
“Feeling unsupported by seniors increases self-doubt in new PhDs.”
 
Ask yourself for each theme: “So what? What does this explain or reveal?”

8. Use quotes wisely – not as decoration

A good quote should:
Be short and sharp
Clearly illustrate the point you’re making
Be followed by your interpretation
 
Don’t let quotes do all the work. Your job is to connect them to the story.

9. Aim for clarity, not complexity, in your writing
 
If your methods and findings can’t be understood by a smart Master’s student, they’re probably too complicated.
 
Avoid filler phrases like “It is important to note that…” – be direct and specific.

PS:  What part of qualitative research do you struggle with most –
 interviews, coding, or writing up themes?

Share in the comments.

REPOST to help others.

Guide to using Qualitatuve Research Methodology

The biggest research mistake?
Choosing a topic before choosing a problem.

A well-crafted research question is not just a sentence… it is the backbone of your entire research project.

Here are simple, practical tips to help you write research questions that are clear, focused, and worth answering:

1. Start with the Problem, Not the Literature Dump 
Don’t begin by thinking, “What topic should I choose?”
 
Start by asking: “What real-world problem or gap actually needs to be solved or understood?”

Your research question should grow from a problem that genuinely puzzles you.

2. Make Your Question Answerable 

A great research question is:
 ✔ Specific
 ✔ Narrow
 ✔ Observable
 ✔ Measurable (even in qualitative research, “measurable” means “can be explored through data”)

Avoid questions like:
 ✖ “Why is education important?”
 That’s an essay, not research.
 
Instead aim for:
 ✔ “How do first-year teachers experience the shift to AI-assisted classrooms?”

3. Choose the Right Question Type
Ask yourself: What exactly do I need to know?

For quantitative studies → your question usually aims to:
• Compare groups
 • Test relationships
 • Measure an outcome
Examples:
 ✔ “Does training frequency predict employee retention in startups?”
 ✔ “Is there a difference in burnout levels between remote and on-site nurses?”

For qualitative studies → your question usually aims to:
• Explore experiences
 • Understand meanings
 • Unpack processes
Examples:
 ✔ “How do women describe their decision-making process after receiving an infertility diagnosis?”
 ✔ “What challenges do teachers face when integrating assistive technology for autistic learners?”

4. One Question = One Direction
A common mistake: asking questions that are trying to do too many things at once.
Keep your RQ laser-focused.

If you feel tempted to add “and” again and again — split it into sub-questions.

5. Make Sure Someone Actually Needs the Answer
A strong research question has impact.

Ask yourself:
 👉 If I answer this, who benefits?
 👉 Does this move the field forward?
 👉 Will this help someone make better decisions?
If the answer is “not really,” revise it.

6. Let Your RQ Guide Your Entire Design
This is the part most students underestimate.
 Your research question should naturally lead to:
 • Your methodology
 • Your sampling decisions
 • Your analytical strategy
 • Your hypotheses (if quantitative)
 • Your interview questions (if qualitative)
If your question doesn’t point clearly to the method, there’s a mismatch.

7. Don’t Aim for Perfect — Aim for Clear
Research questions evolve.

Refining your RQ is part of the research process, not a sign that you're doing it wrong.

PS: What’s one mistake you made when framing your first research question — and what did it teach you?
Share in the comments.

REPOST to help others.

Guide to writing RQ and hypothesis

Most PhD students overthink the results section…
But do you know where reviewers decide whether your paper is strong?

The Introduction.
Because if your Introduction is weak, unfocused, or confusing…
your reader is already gone before you show them your brilliant work.

Below are the guidelines, I wish every researcher knew about writing a powerful Introduction:

1. Start with the big picture, not the details
Give your reader a clear map.
Set the broad context: Why does this topic matter?

Think of it as the “invite” to your research.

2. Narrow it down step by step
Move from general → specific.
 
Show the logical flow from the broader problem to the exact issue you are addressing.
If your introduction feels like a jump-scare, you wrote it too fast.

3. Highlight what we already know (briefly)
Summarise key literature, not everything you read.

Pick the 4–6 most relevant findings that lead directly to your research gap.

4. Make the research gap unmistakably clear
This is where 80% of papers fail.
 
Explain what is missing, unclear, or contradictory in the current knowledge.
 
Your gap should be specific, not a generic statement like “few studies have explored…”.

5. Show why your study matters
Tell the reader why this gap is worth addressing:
 
Does it solve a real problem?
Challenge old assumptions?
Improve practice or policy?

6. State your aim and research questions clearly
 
One sentence for the aim.
One or two questions or hypotheses.
No jargon, no long stories.

7. End with a mini-roadmap
Briefly outline what comes next:
 “This paper next discusses the methodology, followed by results and implications…”
It helps the reader stay oriented and improves clarity.

PS: What's your biggest struggle with introductions?
Share in the comments.

Introduction Section for Research Papers

How to cut your literature review time from 6 weeks to 6 hours (without missing the important papers) ?

Most PhD students don’t struggle with ideas 
They struggle with information overload.

You open databases for 10 minutes… and 3 hours + 27 tabs later, you’re still not sure what the field actually says.

This is where this Literature Review Agent + Research Tracer together can be genuinely helpful, without replacing your brain.

How I tell my mentees to use them:
1. Go to https://lnkd.in/eiHTBi36
2. Start wide with the Literature Review Agent. 

Type your topic
✅ It searches through over 200 million academic papers to highlight key works in your field and identify research gaps. 
✅Instead of spending weeks wondering if you've covered the foundations, you get a clear map of the landscape in minutes.

Treat this as a map of the territory, not the final word. Mark which themes actually match your research question.

3. Then zoom in with Research Tracer
Once you know the main themes, use Research Tracer for:

✅Tracing how ideas evolved over time
✅Seeing which papers started a line of work – and which ones challenged it
✅Spotting newer trends and shifts you might miss with manual searching 

Start with the Literature Review to understand the big picture and spot the gaps. 
Then use the Research Tracer to follow the thread of specific concepts that matter to your work. 

You can even feed it your rough notes (up to 2,500 characters) and it'll find papers in the same domain to compare against what you've written.

📌 Even with both agents, you still need to:
Read the important papers yourself (methods, limitations, not just the abstract)
Check that citations actually support the claims
Decide which debates matter for your thesis
Rewrite all AI outputs in your own words and voice

Think of these agents as research assistants who help with the heavy lifting of searching, tracing, and organising so you can spend more time thinking, critiquing, and writing.

If you’re a PhD or early-career researcher:
 👉 Use AI to cut down search time, not thinking time.

Try it here: https://lnkd.in/eiHTBi36
 40% off the first month only valid for the Liner Pro monthly plan.
 Use code: 2025priya1 for the final discounted price.

PS: How many literature reviews have you started over because you weren't sure you'd covered everything?

Share in the comments

REPOST to help others

How to write a review that journals actually want to publish??

Review studies look straightforward… until you start one.

Very quickly, you realise they demand more organisation, more clarity, and more discipline than almost any other research design.

Here are a few things I wish, I knew earlier about literature reviews, scoping reviews, systematic reviews, and meta-analyses:

1. Your review is only as strong as your question
Most researchers jump into searching before sharpening their question.
 
But a vague question = vague search = vague conclusions.

A tight question instantly tells you:
what to search,
what to ignore,
and which type of review makes sense.
Think of the question as your GPS, if it's unclear, expect detours.

2. Build your “evidence pipeline” before you search
A good review is 50% planning, 50% execution.

Before touching a database, set up:
where you’ll store papers,
how you’ll label and code them,
who checks what,
and what happens if you disagree on a study.

This upfront setup saves you from chaos later.

3. Don’t aim for perfect, aim for transparent
Review studies often trigger perfectionism: “what if I missed a paper?”
 
Instead of perfection, focus on clarity.
If your process is:
logical,
well-documented, and
reproducible,
…your review holds up even if you refine it later.

Transparency beats perfection.

4. The magic happens after you extract the data
Most beginners think the hard part is screening.

It’s not.
The real challenge begins when you have 40–80 papers and must turn scattered findings into a clear story. 

That requires:
pattern-spotting,
grouping ideas,
comparing contradictions,
and identifying what the field still doesn’t know.

This is where your analytical voice shines.

5. Use your review to discover, not just to summarise
A high-quality review doesn’t simply restate what others said.
 
It tells the reader:
what’s missing,
where the evidence is thin,
where the field is confused,
and what the next research step should logically be.

The purpose is not to show everything you read, but to create clarity for someone who hasn’t read any of it.

6. Design your review for your future self
Reviews take months.

Document decisions as if someone else will continue your project tomorrow:
Why did you exclude that study?
Why did you choose that database?
Why did you change your keywords?

Your future self will thank you.

7. And finally: pace yourself
Review studies can be surprisingly draining.

Set:
weekly screening goals,
a time limit for reading each abstract,
and clear “stop” criteria.

Slow and steady > burnout and backlog.

PS: Do you prefer reading 100 papers before you write or writing as you read?
Share in the comments.

REPOST to help others.

How to find the papers you didn’t even know you were missing?

Most researchers don’t struggle with finding papers.

They struggle with making sense of the papers they’ve already found.

You collect PDFs, bookmark links, highlight paragraphs…
but when it’s finally time to connect the dots, the literature feels scattered and overwhelming.

That’s exactly where AnswerThis (YC F25) Canvas surprised me.

It’s not just another AI tool — it’s a full research system:
Search → Analyse → Chat → Map → Write all in one clean interface.

How I used it for a citation map:
I started with a simple research question.
 
Canvas instantly generated a literature review with real citations, then surfaced additional studies I hadn’t even thought to include.

This is where it gets genuinely useful:
 you can filter, trim, and refine the papers until you’re left with exactly the set you want to analyse.

Then, with one click, you can run a bibliometric snapshot showing:
Which years had publication spikes
Which keywords dominate the field
Who the influential authors are
Which studies have shaped the conversation

And my favourite part?

You can visualise how 50+ papers connect —
which ones are central, which ones sit on the edges, and which foundational studies you might have overlooked.

It’s like watching your literature review untangle itself.

Try this workflow, here’s the link: https://lnkd.in/e_HfEfN8 

PS: Would a citation map change how you approach your next paper or PhD chapter?

Share in the comments

REPOST to help others.

Google quietly released a new AI-powered research tool

Google Scholar Labs, an experimental AI-powered feature that actually understands your research question and brings back papers with context. 

If you’ve ever spent hours searching, clicking, and still missing key literature… this tool might change your workflow.

In my new video, I break down:
✨ What Scholar Labs is
 ✨ How the AI-powered search works
 ✨ A full demo using real research questions
 ✨ When to use it (and when not to)
 ✨ How to save hours in your literature review

If you’re a PhD student, early-career researcher, or anyone doing academic writing — this is worth knowing.

🎥 Watch the full video here: https://lnkd.in/eNintd5Q

PS: Do you think AI will become a standard part of academic literature searching in the next 2–3 years?
Share in the comments.

REPOST to help others.

The biggest determinant of PhD success? 

Not your GPA. Not your topic. Not your supervisor. 

Your resilience.

When I look back at my own PhD, I remember a moment that completely changed how I understood progress.

It wasn’t during a breakthrough.
It wasn’t after a great supervision meeting.
It wasn’t even when a chapter finally clicked.
It was during a period where I had completely burned out... a quiet afternoon where I sat staring at my laptop, unable to even open the document.

At that moment, I didn’t need a productivity strategy.
I didn’t need a new writing tool.
I didn’t need a better timeline.
I needed recovery.

And no one had ever told me how crucial that was.

Over the years, supervising students, I’ve realised something powerful:

The students who finish strong are the ones who know how to come back after they fall.

Because in a PhD, you will fall.

Not once.
Not twice.

But repeatedly, and in ways that feel personal.

You will go through:
 • intellectual droughts
 • confidence crashes
 • emotional exhaustion
 • rejection after months of effort
 • life moments that interrupt everything
 • days when every sentence feels wrong

📌 The overlooked skill that carries you through a PhD is:
Knowing when to pause.
Knowing how to restore your mind.
Knowing how to speak to yourself with kindness when you feel behind.
Knowing the difference between discipline and self-punishment.
Knowing that rest is not time lost, it is part of the process.

🔥 My message to PhDs today:
Your capacity to keep going will not come from working harder.
It will come from restoring your ability to think, feel, and function.

Because research is not a sprint.
It’s not a marathon either.

It’s a long, uneven landscape full of climbs, dips, plateaus, and unexpected storms.

Success belongs to those who learn how to rest without quitting.

PS: What does recovery look like for you and when was the last time you allowed yourself to do it without guilt?

Someone else reading the comments might need your answer.

Share in the comments

REPOST to help others.

“How do I start this sentence?” 

If you’ve ever stared at a blank screen wondering, you are not alone.

Academic writing involves both good ideas and finding the right language to communicate them with clarity and precision.

This guide of starter phrases for all major sections of a research paper, and it reminded me how powerful syntactic scaffolding can be.

Thank you for sharing Muhammad Muneeb

Sometimes, we don’t need new ideas, we just need the right sentence structure to express them.

This resource offers such practical, ready-to-use phrasing 👇 

Save this for later. 

REPOST to help others

The EduTech Guide: AI Transformations in Learning | Your AI guide to the digital world | Follow me to learn how you can use AI to 10x your productivity and accelerate your career.

100 starter phrases for research writing.

I personally found this guide very useful for writing.

This guides you how to write each of the following sections.

- Introduction
- Literature review
- Methods
- Results
- Discussion 
- Conclusion

#phd #research #writing

Research writing

Biomedical science finally gets an AI built just for its complexity

Meet the SciSpace BioMed Agent 
What impressed me most is how purpose-built it is.

With 150+ biomedical software integrations and 100+ specialized tools, 
it can automate tasks that normally require multiple platforms and a lot of manual effort.
 
Clinical workflows, 
variant interpretation, 
literature review, 
experimental design, 
drug discovery… all in one place.

The original SciSpace Agent still handles broad research across all disciplines.

But BioMed Agent is built only for biomedical work, from genes and pathways to patients, drugs, and trials. 

It understands the language, the complexity, and the workflow.

To test it, I asked a real research question:
 👉 “Show me recent studies, biomarkers, therapeutic targets, and ongoing clinical trials for Duchenne Muscular Dystrophy.”

And it delivered — structured, clear, up-to-date insights within seconds.
 
I also tried the new biomedical illustration feature 

I simply prompted it to create a clinical trial phases diagram… and it generated a clean, publication-ready figure instantly.

For someone who has spent years making figures for papers and lectures, this felt like magic.

If you’re in biomedical research, this isn’t just another tool.

It genuinely feels like having an AI co-scientist—one that saves you hours, reduces cognitive overload, and helps you focus on the work that actually matters.

🔗 Try SciSpace BioMed Agent : https://lnkd.in/eieAfd-5
Use code:
DPSBIO40: offer 40% off on annual plan
DPSBIO20: offer 20% off on monthly plan

DPSBIO30: offer 30% off on annual plan (Indian users)

PS: If AI could automate ONE step of your biomedical pipeline this week, what would you choose?

Share in the comments

REPOST to help others.

#scispace #scispacebiomed #aiinresearch #biomedicalscience #researchtools #phdlife #drugdiscovery #clinicalresearch

❓ Mam...“How do I use AI to support my research without letting it override my own thinking?”

Most researchers I mentor ask this similar question now 👆 

I believe the answer lies in the workflow.

Recently, I experimented with AnswerThis (YC F25) simply to understand how such systems might support early-stage exploration, especially the thinking before writing phase. 

That exploration led me to sketch a simple, ethical framework that any researcher can adapt.

A Suggestive Framework for Using AI in Early Research Thinking:

Draft → Extract → Evaluate → Interpret → Rewrite

1. Draft (AI for scaffolding only)
Tools like AnswerThis (YC F25) can generate a very rough first draft or outline based on a research question.
 
This isn’t the end product.
It’s a starting structure.
 
It helps researchers see how the field might be framed before they begin shaping it themselves.

2. Extract (AI for organising information)
One feature I found quite useful was the ability to extract limitations, gaps, and future directions from the papers AI itself cited.

It’s simply about accelerating the information-gathering phase so you can spend more time thinking and less time manually hunting for recurring themes.

3. Evaluate (human verification is essential)
Every AI-generated insight must be checked against the original papers.

Accuracy, nuance, context 
that responsibility remains yours.
 
AI can summarise, but it cannot read like a researcher.

4. Interpret (the core intellectual work)
Your analysis determines:
✅ which gaps are meaningful
✅how ideas connect
✅what questions matter
✅where a study could contribute

This is where your voice, expertise, and originality shape the argument.

5. Rewrite (claim the draft as your own)
Even if AI helps produce scaffolding, the final text should be your reasoning, your words, your structure.

This framework matters, as:
It keeps the researcher at the centre.
 
It uses AI for the parts that slow you down — summarisation, structuring, organising 

while protecting the parts that define scholarship:
judgment, interpretation, and argumentation.

For me, this reframes AI not as a shortcut, but as a thinking partner during early exploration.

If you want to try the workflow with AnswerThis, go here: https://lnkd.in/e_HfEfN8 
For discounts on subscription, use 'PRIYA10'

PS: Are you experimenting with tools like AnswerThis for early drafts or deep dives?
What boundaries or workflows help you keep the research rigorous and ethical?
Share in the comments.

REPOST to help others.

Follow for more research workflows.

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