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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 Edinburgh 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 Edinburgh
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend virtual meetups, and connect on LinkedIn. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to machine learning and data privacy. We want to see your hands-on experience, so make sure it’s easy for potential employers to find and understand your work.
✨Tip Number 3
Prepare for interviews by brushing up on technical questions and case studies relevant to ADMET and ML architecture. We recommend practising with friends or using mock interview platforms to get comfortable with the format and types of questions you might face.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
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 Edinburgh
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 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 Technical Skills: In your application, don’t forget to showcase your technical skills, especially in ML architecture and experimentation. Mention any experience with graph neural networks or transformers, as these are key to the role. We love seeing candidates who can hit the ground running!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get all the updates. Plus, it shows you’re keen on joining our mission-driven team at StudySmarter!
How to prepare for a job interview at Owen Thomas | B Corp™
✨Know Your Stuff
Make sure you’re well-versed in the latest machine learning techniques, especially those relevant to ADMET and structural biology modelling. Brush up on graph neural networks and transformers, as these are key to the role. Being able to discuss your past projects and how they relate to data privacy will show that you’re not just a theorist but someone who can apply knowledge practically.
✨Showcase Your Collaboration Skills
Since this role involves working closely with leadership and mentoring others, be prepared to share examples of how you've successfully collaborated in the past. Highlight any experience you have in cross-functional teams or partnerships, especially in a remote setting. This will demonstrate your ability to influence technical direction without direct management.
✨Prepare for Technical Questions
Expect to dive deep into technical discussions during your interview. Prepare to explain your approach to designing ML solutions, particularly around data security and privacy. Think about potential privacy attack-surface assessments you’ve conducted and be ready to discuss your methodologies and findings.
✨Engage with Their Mission
This company is mission-driven, so it’s crucial to align your values with theirs. Research their work in life sciences and drug discovery, and be ready to articulate why you’re passionate about contributing to this field. Showing genuine interest in their mission can set you apart from other candidates.