At a Glance
- Tasks: Lead innovative research in machine learning for materials science and automate experiments.
- Company: Generative, a pioneering AI lab based in London.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Exciting environment with potential for significant career advancement.
- Why this job: Join a cutting-edge team and make a real impact in AI-driven discoveries.
- Qualifications: Strong background in machine learning and experience in collaborative research.
The predicted salary is between 60000 - 80000 £ per year.
Generative, a London-based early-stage AI lab, is seeking a Research Scientist, Machine Learning.
You will own research problems at the intersection of modelling, reasoning and experiment automation, driving an AI-driven discovery engine for materials science.
You will design novel ML approaches, develop active learning methods, translate scientific constraints into mathematical models, and collaborate with scientists to bring ideas from theory to production-ready code.
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Machine Learning Research Scientist — Equity & Impact in London employer: Generative
As a Machine Learning Researcher at our London-based AI lab, you'll be part of a dynamic and ambitious team dedicated to solving significant scientific challenges through innovative AI solutions. We foster a collaborative and inclusive work culture that values curiosity and low ego, offering flexible hybrid working arrangements and opportunities for professional growth in a supportive environment. Join us to make a tangible impact from day one, as you contribute to cutting-edge research that accelerates the discovery of commercially valuable materials.
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We think this is how you could land Machine Learning Research Scientist — Equity & Impact in London
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We think you need these skills to ace Machine Learning Research Scientist — Equity & Impact in London
Some tips for your application 🫡
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Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
