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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.
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 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 Portsmouth 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 Portsmouth
✨Tip Number 1
Network like a pro! Reach out to folks in your field on LinkedIn or at industry events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨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 do.
✨Tip Number 3
Prepare for interviews by brushing up on technical questions and case studies relevant to drug discovery and ML. Practice makes perfect, so get a friend to quiz you!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of exciting roles, and applying directly can sometimes give you an edge over the competition.
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 Portsmouth
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 privacy, 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 helps us keep track of applications and ensures you’re considered for this exciting opportunity at StudySmarter!
How to prepare for a job interview at Owen Thomas | B Corp™
✨Know Your Stuff
Make sure you brush up on the latest techniques in machine learning, especially around ADMET and structural biology modelling. Be ready to discuss your hands-on experience with graph neural networks and transformers, as well as any relevant projects you've worked on.
✨Showcase Your Privacy Knowledge
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 privacy measures in past projects. This will show that you can lead the technical direction effectively.
✨Collaborative Spirit
Highlight your experience in collaborative model development and how you've worked with cross-functional teams. Discuss any mentoring roles you've taken on, as this position involves influencing others without direct management.
✨Research and Publications
If you've authored scientific publications or contributed to open-source software, make sure to mention these during the interview. It demonstrates your commitment to advancing the field and your ability to communicate complex ideas effectively.