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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 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.
Principal Machine Learning Researcher (Privacy/Risk) | Series A - Drug discovery Platform | Fully Remote, EU/UK | Base Salary , plus early equity+benefits in Chesterfield 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 Chesterfield
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend virtual meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to machine learning and data privacy. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on technical questions and case studies relevant to ADMET and ML architecture. Practice explaining complex concepts in simple terms, as this will help you communicate effectively with both technical and non-technical interviewers.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, applying directly shows your enthusiasm and commitment to joining our mission-driven team.
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 Chesterfield
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.
✨Privacy Matters
Since this role focuses heavily on data privacy, be prepared to talk about your understanding of privacy attack-surface assessments and how you've implemented data security in previous roles. This will demonstrate your alignment with the company's mission-driven approach.
✨Collaborative Spirit
Highlight your experience in collaborative environments, especially in research settings. Discuss how you've worked with cross-functional teams or partnered with other organisations, as this role involves significant collaboration in model development.
✨Show Your Impact
Prepare examples of how your work has influenced technical direction or led to significant advancements in your field. Whether it's through publications or open-source contributions, showcasing your impact will resonate well with the interviewers.