Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Lead ML solutions for drug discovery, focusing on data privacy and innovative modelling techniques.
- Company: Mission-driven tech company in life sciences, fully remote opportunities across EU/UK.
- 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 advancing your career in a cutting-edge field.
- Qualifications: Experience in machine learning, computational chemistry, and strong problem-solving skills.
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 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.
3 Month Plan: - Develop a working understanding ...
Principal Machine Learning Researcher (Privacy/Risk) | Series A - Drug discovery Platform | Fully Remote, EU/UK | Base Salary , plus early equity+benefits in Leigh 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 Researcher (Privacy/Risk) | Series A - Drug discovery Platform | Fully Remote, EU/UK | Base Salary , plus early equity+benefits in Leigh
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend virtual meetups, and connect on LinkedIn. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Prepare for those interviews by practising common questions and showcasing your expertise in machine learning and data privacy. We recommend doing mock interviews with friends or using online platforms to get comfortable with the process.
✨Tip Number 3
Showcase your projects! Whether it’s through a portfolio or GitHub, let your work speak for itself. We love seeing hands-on experience, especially in areas like ADMET modelling and data security.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we’re always on the lookout for passionate individuals ready to make an impact in drug discovery.
We think you need these skills to ace Principal Machine Learning Researcher (Privacy/Risk) | Series A - Drug discovery Platform | Fully Remote, EU/UK | Base Salary , plus early equity+benefits in Leigh
Some tips for your application 🫡
Show Your Passion for the Mission: When writing your application, let us know why you're excited about working in the life sciences and drug discovery. We love candidates who share our mission-driven mindset, so make sure to highlight your enthusiasm for making a difference!
Tailor Your Experience: Don’t just send a generic CV! We want to see how your specific skills in machine learning and data privacy align with the role. Be sure to showcase relevant projects or experiences that demonstrate your expertise in ADMET modelling or similar areas.
Be Clear and Concise: We appreciate clarity! When you’re writing your application, keep it straightforward and to the point. Use bullet points where possible to make your achievements stand out, and avoid jargon unless it’s necessary.
Apply Through Our Website: To make sure your application gets the attention it deserves, apply directly through our website. It’s the best way for us to track your application and ensure it reaches the right people!
How to prepare for a job interview at Owen Thomas | B Corp™
✨Know Your Stuff
Make sure you brush up on the latest trends in machine learning, especially around ADMET and data privacy. Be ready to discuss specific techniques like graph neural networks and transformers, as well as how they apply to drug discovery.
✨Showcase Your Experience
Prepare to share examples of your hands-on experience with ML architecture and experimentation. Highlight any projects where you've led technical direction or collaborated with others, as this role involves significant influence over technical strategy.
✨Understand the Company’s Mission
Familiarise yourself with the company’s mission in the life sciences domain. Be prepared to discuss how your skills can contribute to their goals, particularly in maintaining data privacy and ownership while advancing model applications.
✨Ask Insightful Questions
Prepare thoughtful questions that show your interest in the role and the company. Inquire about their current challenges in data privacy or how they envision the future of ML in drug discovery. This demonstrates your engagement and strategic thinking.