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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.
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 Manchester 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 Manchester
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend virtual meetups, and connect with professionals on LinkedIn. We can’t stress enough how important it is to build relationships; you never know who might have the inside scoop on job openings.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to machine learning and data privacy. We recommend sharing your work on platforms like GitHub or even writing blog posts about your findings. This will make you stand out when applying for roles.
✨Tip Number 3
Prepare for interviews by brushing up on technical questions and case studies relevant to ADMET and ML architecture. We suggest doing mock interviews with friends or using online resources to get comfortable discussing your expertise and experiences.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got some fantastic opportunities waiting for you, and applying directly can sometimes give you an edge. Plus, it’s super easy to keep track of your applications this way!
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 Manchester
Some tips for your application 🫡
Show Your Passion for the Role: When writing your application, let your enthusiasm for machine learning and drug discovery shine through. We want to see how your interests align with our mission-driven approach and how you can contribute to our innovative platform.
Tailor Your CV and Cover Letter: Make sure to customise your CV and cover letter for this specific role. Highlight your experience with ADMET modelling, data privacy, and any relevant ML techniques. We love seeing candidates who take the time to connect their skills with what we’re looking for!
Be Clear and Concise: Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon unless it’s necessary. Make it easy for us to see your qualifications and how they fit with the Principal Machine Learning Researcher position.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it helps us keep everything organised on our end.
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 data privacy. Familiarise yourself with graph neural networks and transformers, as these are key to the role. Being able to discuss your past projects and how they relate to the job will show your expertise.
✨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 research setting.
✨Prepare for Technical Questions
Expect to dive deep into technical discussions during the interview. Prepare to explain your approach to designing ML solutions and how you handle data privacy challenges. Practising coding problems or case studies related to drug discovery can also give you an edge.
✨Ask Insightful Questions
Interviews are a two-way street, so come armed with questions that show your interest in the company's mission and technical direction. Inquire about their current projects in ADMET modelling or how they ensure data security in their federated infrastructure. This not only shows your enthusiasm but also helps you gauge if the company is the right fit for you.