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- Tasks: Lead ML solutions for drug discovery using advanced techniques like graph neural networks.
- Company: Mission-driven tech company in life sciences, focused on innovative drug discovery.
- Benefits: Competitive salary up to £160,000, early equity, and comprehensive benefits.
- Other info: Collaborative environment with significant influence over technical direction and career growth.
- Why this job: Make a real impact in drug discovery while working remotely with cutting-edge technology.
- Qualifications: Experience in ADMET or Structural Biology modelling and strong ML engineering skills.
The predicted salary is between 160000 - 160000 £ per year.
The Client: 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.
Principal Machine Learning Scientist | ADMET/Structural Biology | Series A - Drug discovery Platform | Fully Remote, EU | Base Salary , plus early equity+benefits in Colchester employer: Owen Thomas | B Corp™
Contact Detail:
Owen Thomas | B Corp™ Recruiting Team
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 , plus early equity+benefits in Colchester
✨Tip Number 1
Network like a pro! Reach out to professionals in the life sciences and machine learning fields on LinkedIn. Join relevant groups, attend virtual meetups, and don’t be shy about asking for informational interviews. We all know that sometimes it’s not just what you know, but who you know!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to ADMET or Structural Biology. Whether it's a GitHub repository or a personal website, let your work speak for itself. We want to see your hands-on experience and innovative solutions!
✨Tip Number 3
Prepare for those interviews! Research common questions for Principal Machine Learning Scientist roles and practice your responses. We recommend focusing on your technical expertise and how you can contribute to data privacy and model development. Confidence is key!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search. Don’t forget to tailor your application to highlight your experience with ML architecture and collaboration!
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 , plus early equity+benefits in Colchester
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of Principal Machine Learning Scientist. Highlight your experience with ADMET or Structural Biology modelling, and don’t forget to showcase any hands-on projects that demonstrate your skills in ML architecture and data privacy.
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 aligns with our mission. Be sure to mention specific techniques like graph neural networks and transformers that you’ve worked with.
Showcase Your Collaborative Spirit: Since we value collaboration, make sure to highlight any experiences where you’ve worked closely with teams or partnered with other organisations. This will show us that you can thrive in a collaborative environment while maintaining data privacy.
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 don’t miss out on any important updates regarding your application status!
How to prepare for a job interview at Owen Thomas | B Corp™
✨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 how they apply to drug discovery. The more you can demonstrate your expertise, the better!
✨Showcase Your Hands-On Experience
Since this role is hands-on, be prepared to share examples of your previous work in machine learning and computational chemistry. Talk about projects where you've led the design and implementation of ML solutions, and highlight any challenges you overcame.
✨Emphasise Data Privacy
Given the focus on data security and privacy, make sure you can articulate your understanding of these concepts. Discuss any experience you have with privacy attack-surface assessments or implementing data privacy measures in your models.
✨Collaboration is Key
This role involves working closely with leadership and mentoring others, so be ready to talk about your collaborative experiences. Share how you've worked with cross-functional teams and contributed to a positive team environment, even if it's not a formal management position.