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- 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 a passion for data privacy.
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.
Principal Machine Learning Researcher (Privacy/Risk) | Series A - Drug discovery Platform | Fully Remote, EU/UK | Base Salary , plus early equity+benefits in Glasgow 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 Glasgow
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at conferences. A personal connection can often get your foot in the door faster than a CV.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to ML and data privacy. This gives potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on technical questions and case studies relevant to drug discovery and ML. Practising with a friend can help you articulate your thoughts clearly.
✨Tip Number 4
Don’t forget to apply through our website! We love seeing candidates who are genuinely interested in our mission and values. It’s a great way to stand out from the crowd.
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 Glasgow
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of Principal Machine Learning Researcher. Highlight your experience with ADMET, structural biology modelling, and any relevant machine learning techniques. We want to see how your skills align with our mission in drug discovery!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data privacy and risk in machine learning. Share specific examples of your work that demonstrate your expertise and how you can contribute to our team at StudySmarter.
Showcase Your Projects: If you've worked on any projects related to ML architecture or data security, make sure to include them in your application. We love seeing hands-on experience, especially if it involves collaborative model development or innovative solutions in drug discovery.
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to submit all your materials in one go. Plus, we love seeing candidates who take the initiative to connect with us directly!
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 modelling and the latest in machine learning techniques like graph neural networks and transformers. Be ready to discuss how you've applied these in past projects, as this will show your hands-on experience and technical authority.
✨Showcase Your Privacy Savvy
Since this role focuses heavily on data privacy, prepare to talk about your understanding of privacy attack-surface assessments and how you've implemented data privacy measures in your previous work. This will demonstrate your alignment with the company's mission-driven approach.
✨Collaborative Spirit
Highlight your experience in collaborative environments, especially in research settings. Be prepared to share examples of how you've worked with cross-functional teams or mentored others, as this role involves significant collaboration and influence over technical direction.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's drug discovery platform and their approach to federated data infrastructure. This shows your genuine interest in the role and helps you gauge if the company’s values align with yours.