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- Tasks: Lead ML solutions for drug discovery using advanced techniques like graph neural networks.
- Company: Mission-driven tech company in life sciences, focused on innovation.
- Benefits: Competitive salary up to £160,000, early equity, and comprehensive benefits.
- Other info: Collaborative environment with opportunities for significant technical influence.
- Why this job: Make a real impact in drug discovery while working remotely across Europe.
- Qualifications: Experience in ADMET or Structural Biology modelling and machine learning engineering.
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 Wolverhampton 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 Wolverhampton
✨Tip Number 1
Network like a pro! Reach out to professionals in the life sciences and machine learning fields on LinkedIn. Join relevant groups and participate in discussions to get your name out there and show off your expertise.
✨Tip Number 2
Prepare for those interviews! Research common questions for Principal Machine Learning Scientist roles, especially around ADMET and Structural Biology. Practise articulating your experience with ML architecture and data privacy to impress the interviewers.
✨Tip Number 3
Showcase your projects! Create a portfolio that highlights your hands-on experience with ML solutions, particularly in drug discovery. This will give you an edge and demonstrate your technical authority in the field.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might be perfect for you. Plus, it’s a great way to ensure your application gets the attention it deserves.
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 Wolverhampton
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 research papers, open-source contributions, or personal projects, we want to see how you've applied your skills in real-world scenarios, especially in ML and data security.
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’re considered for this exciting opportunity. Plus, it gives you a chance to explore more about our company culture and values!
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 ML solutions and data privacy. Talk about any projects where you've led technical direction or collaborated with others, as this will highlight your leadership potential.
✨Understand Their Mission
Research the company’s mission and values. They’re looking for someone who aligns with their goals in life sciences and drug discovery. Showing that you understand and are passionate about their mission can set you apart from other candidates.
✨Prepare Questions
Have a few thoughtful questions ready to ask during the interview. This could be about their federated data infrastructure or how they approach model development. It shows you're engaged and genuinely interested in the role and the company.