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- Tasks: Lead ML solutions for drug discovery, focusing on ADMET modelling and data privacy.
- Company: Mission-driven tech company in life sciences, fully remote work culture.
- Benefits: Competitive salary up to £160,000, early equity, and comprehensive benefits.
- Other info: Influential role with significant technical direction and career growth opportunities.
- Why this job: Make a real impact in drug discovery using cutting-edge machine learning techniques.
- Qualifications: Expertise in ADMET or Structural Biology and strong ML engineering 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 (Absorption, Distribution, Metabolism, Excretion, and Toxicity) 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.
Principal Machine Learning Scientist | ADMET/Structural Biology | Series A - Drug discovery Platform | Fully Remote, EU | Base Salary , plus early equity+benefits in Basildon 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 Scientist | ADMET/Structural Biology | Series A - Drug discovery Platform | Fully Remote, EU | Base Salary , plus early equity+benefits in Basildon
✨Tip Number 1
Network like a pro! Reach out to your connections in the life sciences and machine learning fields. Attend relevant webinars or meetups, and don’t be shy about asking for introductions. We all know that sometimes it’s not just what you know, but who you know!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to ADMET or Structural Biology. Use platforms like GitHub to share your code and models. This way, potential employers can see your hands-on experience and technical prowess in action.
✨Tip Number 3
Prepare for those interviews! Research common questions for Principal Machine Learning Scientist roles and practice your responses. We recommend focusing on your problem-solving approach and how you’ve tackled challenges in previous projects, especially around data privacy and ML architecture.
✨Tip Number 4
Apply through our website! We make it super easy for you to submit your application directly. Plus, it shows you’re genuinely interested in joining our mission-driven team. Don’t miss out on the chance to be part of something impactful in drug discovery!
We think you need these skills to ace Principal Machine Learning Scientist | ADMET/Structural Biology | Series A - Drug discovery Platform | Fully Remote, EU | Base Salary , plus early equity+benefits in Basildon
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of Principal Machine Learning Scientist. Highlight your experience with ADMET or Structural Biology modelling, and don’t forget to showcase any hands-on projects that demonstrate your skills in ML architecture and data privacy.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about drug discovery and how your background aligns with our mission. Be specific about your technical expertise and how you can contribute to our collaborative model development.
Showcase Your Projects: If you've worked on relevant projects, make sure to include them in your application. Whether it's a research paper or a personal project, showing off your practical experience with ML solutions for ADMET will definitely catch our eye!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, you’ll find all the details about the role and our company culture there!
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 and Structural Biology. Be ready to discuss specific techniques like graph neural networks and transformers, as well as how they apply to drug discovery. The more you can demonstrate your expertise, the better!
✨Showcase Your Hands-On Experience
Since this role is hands-on, be prepared to share examples of your previous work in machine learning and computational chemistry. Talk about projects where you've led the design and implementation of ML solutions, especially those that involved data privacy and security.
✨Collaborative Spirit
This position involves working closely with leadership and mentoring others. Highlight your experience in collaborative environments and how you've successfully worked with cross-functional teams. Share any instances where you've influenced technical direction or contributed to model development.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's approach to data privacy and federated data infrastructure. This shows your genuine interest in their mission and helps you understand how you can contribute to their goals. Plus, it gives you a chance to assess if the company aligns with your values.