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- Tasks: Lead ML solutions for drug discovery, focusing on data privacy and cutting-edge techniques.
- Company: Mission-driven tech company in life sciences, fully remote opportunities.
- Benefits: Competitive salary up to £160,000, early equity, and comprehensive benefits.
- Other info: Collaborative culture 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 high-tech environment.
- Qualifications: Experience in machine learning, computational chemistry, and data privacy.
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.
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 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
✨Tip Number 1
Network like a pro! Reach out to folks in your field on LinkedIn or at industry events. 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 common ML concepts and privacy challenges. Be ready to discuss how you’d tackle real-world problems in drug discovery.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for passionate individuals who want to make an impact in the life sciences domain.
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
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 projects. 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 how your expertise can contribute to our drug discovery platform. Keep it engaging and personal – we love to see your personality come through!
Showcase Your Projects: If you've worked on any relevant projects, especially those involving ML architecture or data security, make sure to mention them. We’re interested in seeing your hands-on experience and how you’ve tackled challenges in the past.
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. Plus, it shows you’re keen to join our team!
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. Familiarise yourself with graph neural networks and transformers, as these are key to the role. Being able to discuss recent advancements or challenges in these areas will show your passion and expertise.
✨Showcase Your Experience
Prepare specific examples from your past work that demonstrate your hands-on experience with ML architecture and experimentation. Highlight any projects where you’ve implemented data privacy measures or collaborated with cross-functional teams. This will help illustrate your ability to lead technical direction effectively.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the company’s approach to federated data infrastructure and how they ensure data security. This not only shows your interest but also helps you gauge if the company aligns with your values and career goals.
✨Be Ready to Collaborate
Since this role involves mentoring and collaborating with other engineers and researchers, be prepared to discuss your approach to teamwork. Share examples of how you've successfully worked with others to achieve common goals, and express your enthusiasm for fostering a collaborative environment.