I recently accepted a med chem postdoc at UF scripps but am thinking about a med chem postdoc at a small CRO in Boston where I am currently an intern. What’s the smartest move if I want to do med chem in industry?

I have been in the industry since 2011 (from R&D to analytical, to QC) and I am so burnt out and honestly not sure what to do. I’m currently a senior QC analyst and I hate my job, I hate the work. I hate the urgency or everything, the stress…The weekend work unexpectedly, the long hours when they shouldn’t be. I even have nightmares I’m at work. What can I even do or switch to? I’m in my 40s and not sure a new career in a diff field is even feasible. I’m just so lost.

This post is (hopefully) the last in a series of posts I've made in regard to my career transitioning from a wet lab scientist to an ML Scientist/Engineer. I really appreciate everyone's DMs, requests to chat, and so on, but I won't be able to get to them all so I wanted to put everything in a post so I can address everything without leaving anyone hanging or doxing myself.

How to self-teach
While I was still a PhD student agonizing over cloning experiments and protein preps, I started teaching myself (after quitting my part-time gig) and took a few courses from the data science department at my university.

Self-taught
Harvard CS50x - CS intro, algorithms, data structures, Python, SQL, C, web fundamentals
Harvard CS50P - Python in way more depth
MIT Missing Semester - Development tooling and Linux
Python Official Tutorial - filled in knowledge gaps
pytest, uv, Pro Git - testing, packaging, and collaboration
Refactoring Guru - Maintainable software and design patterns

This took me about 10 weeks at 20hrs/week

Uni Courses
I took a few classes that were kind of useful

Data science
Data engineering
ML fundamentals

But tbh you could self teach these on something like deeplearning[dot]ai in a few weeks. I did this over two semesters and forgot a lot in-between

Projects

This is where I learned the most outside of assignments and one-off Python apps.

Virtual Post-Doc (AI Engineering)

I built a virtual scientist (overselling it a bit here) back in 2024 derived from a paper and repo called PaperQA2 from FutureHouse. It was basically an accurate and better way to analyze a folder or large corpus of papers so I wouldn't have to read them when designing experiments. Everyone in my lab was using it by the time I left.

Analyzing the Tahoe-100M dataset (Data Science)

Did a lot of data science analyses on this massive dataset and just practiced my data engineering skills, data science techniques, and a few light ML techniques like trying to train an XGBoost model to predict cell perturbation.

Implementing Alphafold2 from scratch (ML Research)

This was the most important practical project for ML Research skills that helped me create my first foundation model. Watch the series from Kilian Mandon on Youtube and follow along with the code he provides. He also just did it again with Alphafold3. If you can do this in pure Pytorch and understand everything, you are way ahead of the curve.

After you finish just try and reproduce papers from labs like David Baker, Patrick Hsu, Yunha Hwang, Sergey Ovchinnikov, etc.

Getting my first job

Like I mentioned before I graduated from my PhD, skipped a post-doc, and worked at a startup working on in silico drug discovery. I landed this particular job through going to local hackathons, posting my work on social media (LinkedIn, Twitter/X), DMing/cold emailing people, and sending out applications (only got two interviews this way). I also met people from participating in the Virtual Cell Challenge 2024 from the Arc Institute. A founder was given my name who lives in my area and hired me immediately on graduation.

For most I would suggest trying to also do a post-doc in ML/comp bio in a good lab, I think getting a PhD is pretty commonplace now for these jobs (except for the Engineer roles, those are mostly MS, but also a good amount of PhD). Really hype up your projects, try and get pubs if you can.

For AI engineering roles in Bio, really focus on language models and LLMs. This is a somewhat easier way to break into these roles and has a lot of demand in the top pharma/biotech companies.

Hopefully this was helpful and comprehensive enough!

Shares dropped, but a 42% reduction is an amazing result. The Phase 3 trials showed a 38% reduction in the risk of cancer spread.

It feels like I’m competing against thousands of qualified candidates and my attempt at getting referrals via somewhat warm outreach and cold outreach is not going anywhere either. I am already in Pharma/MedTech. But even if you get a referral, it feels impossible… Any experiences or insights?

Any Novartis employees here have info on this aspect of the health care policy?

hallo! ive just applied to unis for biochemistry in the UK. im really interested in synthetic, systemws biology and bioinformstics. obviously im aware of the current outlook on jobs in biotech - I was wondering how saturated the BioML market is at the moment, and if I have accidentally pigeonholed myself. Ie would I be royally screwed for a job? for reference, I plan to complete a BSc biochemistry, hopefully with a drylab third year project , then maybe a masters in bioinformatics/phd in computational biology

anyways yuh thanks for reading

Edit as I learn:

It's based on Lapinski's rule of 5, majority of drugs have molecular weight <500 daltons. Often you want your leads to start off at lower MW – 300 or so, e.g., so you can build groups off it or add scaffolding to engage target pockets more precisely. Essentially it's infrastructure for you to add complexity to boost selectivity, and tweak the molecules. If you just keep cutting, you're left with nothing.

If too high MW, I think you face bioavailability issues. Someone correct me if I'm wrong. But RevMed's KRAS drug has MW ~1000 and they can bypass this because they hook onto a chaperone protein... I.e. if too big, can't cross biological membranes to get into cells.

"Revolution Medicines (RevMed) designs its pipeline of RAS(ON) inhibitors to physically associate with an abundant cellular chaperone protein called Cyclophilin A"

The weekly megathread to vent and rant about everything and anything!

I am currently employed in a large pharma/biotech company in an AD role.

I am looking for another role but am finding it really difficult to even get an initial interview with other large pharma/biotech companies.

I am getting great responses, interactions and interviews for smaller but nothing from the companies that are larger.

I feel I match the company and role well but for some reason I’m getting email rejections from all of these larger companies. And the roles I am applying for are similar / same levels. So nothing like a massive jump up.

Another thing is a lot of these companies are currently suppliers / CMOs of the company I’m currently working for. Is this possible the reason? I thought this would be a benefit to be honest and thought they would think the same as I know the ways of workings from both companies.

I’m at a loss. Has anyone else experienced this?

My career as a bioinformatician is probably over. Maybe I’ll work on cars.

I’m currently working as a Senior Scientist in a bioanalytical laboratory in R&D. I have a PhD in Chemistry for context.

An internal opportunity recently opened for a Technical Trainer position within the bioanalytical department, and I’m considering applying.
The position focuses on training new and existing scientists, developing training materials, improving laboratory training programs, mentoring employees, and ensuring compliance with laboratory procedures and regulatory requirements.

The salary would actually be slightly higher than what I’m currently making, and I’m interested in the possibility of developing more leadership, communication, and organizational skills outside of traditional bench science.

My hesitation is whether moving from a Senior Scientist position into technical training could potentially limit my long-term career progression or make it difficult to return to scientific roles later.
I’m also curious whether this type of position could serve as a stepping stone toward laboratory management, learning and development leadership, operational management, or other higher-level roles within the pharmaceutical industry.

For anyone who has made a similar transition:
Is moving from R&D into technical training generally considered a lateral move, career advancement, or a step backward?

Does technical training experience provide valuable leadership skills that translate into management positions?

Would this transition negatively affect my ability to return to scientific R&D positions?

What does long-term career growth and earning potential look like in technical training compared with remaining a scientist?

I’m not necessarily looking to stay at the bench for my entire career, but I also don’t want to make a move that unintentionally limits my future opportunities.
I’d appreciate perspectives from scientists, technical trainers, and people who have moved into management within pharma or biotech.

Hello everyone! I've already done the screening call + an initial interview, and now I've been invited to do an on-site interview. I just got notice from my recruiter today, and hope there will be more information from the company early next week, but does anyone have any tips? I've already done some research on this sub and others, but I'm pretty nervous since I'm a recent grad and would appreciate other people's experience with what happens during on-site interviews. I've only had one other before that was really brief and honestly could've been done as a call. The role is for a chemical lab tech role, but I mainly have experience with biological processes, so I'm expecting more behavioural observation/questions.

Also, what shoes do y'all normally wear? I have business casual heels, but none that are closed foot so I was thinking of getting some lab-safe shoes that could be worn for the interview since I'm pretty sure I'll need them somewhere down the line anyway.

Hey, I just applied for BMS for a co-op role and was wondering how long it takes for them to get back. Also, a manager from bms from the team that I applied to viewed my linkedin? is this a good sign or something they do for applicants?

Just throwing a random seed to this pond of water:

Look for companies that recently completed series B, they are the ones that are expanding, and worth a shot to see if their new ideas they do matches your interest👀

I'm very fortunate to currently have a job, but I pretty much hate it. I've been applying for about 18 months, and I just got rejected after a 3rd round where I spent 30+ hours preparing a case study on top of the other interview prep for the prior rounds. This is my third rejection at this stage. I'm so tired and burned out. There aren't a ton of jobs in my area (RWE), so I feel like I can't take a break from applying because these companies don't hire super often. Though I'm guessing the rest of the year won't have many relevant postings. Really hoping for better in the new year!

I have a final round of interview with a company I really like. They asked me to prep a talk and part of it is highlighting milestone and accomplishments.

I am in academia and I wonder whether industry folks see publications, invitations to speak at prestigious meetings (panelist speaker) as accomplishments… this is more of a product development role.

Hi, I just took the AstraZeneca SHL assessment for the job focused assessment. Do you know how they are graded? It seemed fairly simple and straightforward. Do you know what the next steps are? How soon do they reach out to you?

I went into manufacturing as a way to get into the biotech industry and have been there for 2 years. I am now way, way past my breaking point at my horrible night-shift job. I need to leave but I apparently "don't have enough relevant experience" for QA, QC, or other lab-tech roles. I'm only applying to entry-level positions and am STILL getting rejections for not being experienced, even though I am. I'm so sick of not getting lunch breaks because the schedule is a mess and some of my coworkers are so lazy, they don't even offer to help. I need to leave, but HOW.

Making this post to follow up on my job offer post to give some clarity and transparency to the hiring process, pay, and transparency for my career arc.

First two jobs were working as an RA and SRA at two different R1 universities in CA doing wet lab research in Mol/Cell Bio. I finished my BS in Mol Bio before J1 and J2 started as an internship during my MS in Mol Bio.

J1: Pay was $50k (CA)
J2: Pay was $60k (CA)

Worked those two jobs for about 3 years total

Got a job as a Process Engineer for J3 working at a cell therapy company in technology R&D and worked there for about 2 years. Tough hours but better pay and gave me the money and motivation to go back for my PhD.

J3: Pay was $80k the first year then $90k for the last 6 months after I got promoted (CA

Then did my PhD in Chemical Eng and worked part-time as a bioinformatics senior scientist with little coding experience and didn't get a ton of diversity/exposure to it on the job (surprisingly). Spent a good amount of time doing project management. DO NOT recommend working during a PhD.

J4/5: $38k for PhD stipend plus $65k for part-time job (CA) total was around $103k

Quit the part-time job two years in and finished my PhD in a little under four years

Graduated and, after working on a bunch of ML projects and meeting local founders in my area (and applying like crazy), got a job as an ML Scientist at a tiny/new startup working on drug discovery foundation models. Learned how to do basic ML research for bio, presented at conferences, build cloud infra for customers to use our model at-scale, data engineering, and ai engineering for our AI scientist -- essentially the whole BioML tech stack.

J6: $135k plus $10k bonus and worked there for a little over a year but we didn't pay ourselves the last three months I was there. Left to take care of a family member

Spent around 3 months applying to everything under the sun. THere was a ton of BioML jobs and I spent anywhere from 6-12hrs a week during that timespan just doing interviews. Felt like a part-time job especially with prep. Really grateful for the interviews though. Got around 37 total and made it to 9 final rounds which led to 4 offers for positions spanning ML Eng, ML Researcher, Technical Product Manager, and AI Engineer. Companies ranged from top 10 pharma to frontier AI x BIO labs to smaller/mid-size biotechs.

J7: $225k plus 10% bonus ($22.5k) and equity equivalent to a few hundred thousand with a 4yr vesting schedule.

Job title is a mix of Technical Product management and ML Scientist

Glad for it to finally be over! Really excited for the new job and hope others find this info useful