At a Glance
- Tasks: Lead ML solutions for drug discovery, focusing on ADMET modelling and data privacy.
- Company: Mission-driven tech company in life sciences, fully remote and innovative.
- Benefits: Up to £160,000 salary, equity options, flexible hours, and remote work.
- Other info: Collaborative environment with significant influence over technical direction and career growth.
- Why this job: Make a real impact in drug discovery with cutting-edge machine learning technologies.
- Qualifications: PhD in computational chemistry, 5+ years in drug discovery, and hands-on modelling experience.
The predicted salary is between 160000 - 160000 £ per year.
A mission-driven technology company operating in the life sciences domain is seeking a Principal Scientist - hands-on with either ADMET or Structural Biology modelling, ML engineer to lead the technical direction for ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) modeling efforts within its drug discovery platform. The organisation enables collaborative model development across partner organisations while maintaining strict data privacy and ownership, using a federated data infrastructure.
In this hands-on, high-impact role, you'll work at the intersection of machine learning, computational chemistry, and applied research to advance foundational model applications in drug discovery. You'll be the technical authority on ML architecture, experimentation, and strategy, while focusing specifically on data security and privacy. You will also collaborate closely with leadership and mentor other engineers and researchers. While this is not a people management position, it offers significant influence over technical direction.
Responsibilities:- Lead the design and implementation of ML solutions for ADMET using cutting-edge techniques such as graph neural networks and transformers.
- Lead the research and implementation of data privacy within the models and establish privacy attack-surface assessment.
- Develop and extend models for specific applications, including data distillation, benchmarking, and evaluation.
- Define preprocessing and harmonization strategies for diverse assay datasets used in ADMET modeling.
- Author or contribute to scientific publications or open-source software where appropriate.
- Develop a working understanding of the product, federated training setup, and key life-sciences modelling use cases.
- Reproduce and extend at least one existing modelling pipeline to establish a baseline privacy and attack-surface assessment.
- Contribute to privacy analysis for one or more active federated drug discovery programs as they transition from setup into live operation.
- PhD in computational chemistry or equivalent.
- Drug discovery experience (5y+).
- Hands-on ADMET or Structural Biology modelling experience (broad scope).
- Hands-on experience building an ML based model on public and/or internal pharma datasets in the computational chemistry space.
- Strong understanding of OpenFold, AlphaFold, Boltz and co-folding.
- Confidence in building silico models.
- Excellent communicator and connecting stakeholders; excellent planning capabilities for experimental planning and execution.
- Experience in working in consortium is a plus.
- Fully Remote Working Culture.
- Up to £160,000 Base Salary.
- Attractive Stock Options.
- B2B & Full time employee options.
- Flexible hours +/- 3 hours of CET time zone.
If you think you are a good match for the role, send us your CV and if we think you are a good match, we will give you a call!
Principal Machine Learning Scientist | ADMET/Structural Biology | Series A - Drug discovery Platform | Fully Remote, EU | Base Salary Up to £160,000K, plus early equity+benefits in Ashton-under-Lyne employer: Owen Thomas | B CorpTM
Join a mission-driven technology company at the forefront of life sciences, where you can leverage your expertise in machine learning and computational chemistry to make a significant impact in drug discovery. Enjoy a fully remote working culture that promotes flexibility and work-life balance, alongside competitive compensation, early equity opportunities, and a collaborative environment that fosters professional growth and innovation. This role not only allows you to lead cutting-edge projects but also offers the chance to mentor fellow engineers and researchers, making it an ideal place for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Principal Machine Learning Scientist | ADMET/Structural Biology | Series A - Drug discovery Platform | Fully Remote, EU | Base Salary Up to £160,000K, plus early equity+benefits in Ashton-under-Lyne
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at conferences. A friendly chat can sometimes lead to job opportunities that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to ADMET or Structural Biology. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios specific to machine learning and drug discovery. We recommend doing mock interviews with friends or using online platforms to boost your confidence.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love hearing from passionate candidates like you!
We think you need these skills to ace Principal Machine Learning Scientist | ADMET/Structural Biology | Series A - Drug discovery Platform | Fully Remote, EU | Base Salary Up to £160,000K, plus early equity+benefits in Ashton-under-Lyne
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience in ADMET or Structural Biology modelling. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects and achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about drug discovery and how your background makes you the perfect fit for our team. Keep it engaging and personal – we love to see your personality!
Showcase Your Technical Skills:Since this role is all about ML architecture and data privacy, make sure to highlight your technical expertise. Mention specific tools and techniques you've used, like graph neural networks or transformers, to demonstrate your hands-on experience.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our mission-driven team!
How to prepare for a job interview at Owen Thomas | B CorpTM
✨Know Your Stuff
Make sure you brush up on your knowledge of ADMET and Structural Biology modelling. Be ready to discuss specific techniques like graph neural networks and transformers, as well as your hands-on experience with them. This will show that you're not just familiar with the theory but can also apply it practically.
✨Showcase Your Problem-Solving Skills
Prepare to discuss past projects where you've tackled complex problems in drug discovery. Highlight how you approached data privacy and security in your models, as this is a key focus for the role. Use examples that demonstrate your ability to think critically and innovate.
✨Communicate Clearly
As a Principal Machine Learning Scientist, you'll need to connect with various stakeholders. Practice explaining your work in simple terms, avoiding jargon when possible. This will help you convey your ideas effectively and show that you can mentor others.
✨Be Ready for Technical Questions
Expect in-depth technical questions about ML architecture and experimentation strategies. Prepare by reviewing your previous work and be ready to discuss your thought process behind model development and evaluation. This will demonstrate your expertise and confidence in the field.
