At a Glance
- Tasks: Drive the discovery engine of an autonomous lab using cutting-edge ML architectures.
- Company: Well-funded AI materials discovery startup with top-tier backing.
- Benefits: Opportunity to impact real-world scientific discovery and materials innovation.
- Other info: Join a dynamic team led by world-renowned experts with excellent career growth potential.
- Why this job: Work at the forefront of AI and physical labs, solving critical challenges in materials science.
- Qualifications: PhD in relevant field and expertise in PyTorch or JAX.
The predicted salary is between 60000 - 80000 £ per year.
As a Machine Learning Research Scientist, you will drive the core discovery engine of an autonomous laboratory. You'll develop novel ML architectures, including GNNs and foundation models, to bridge the gap between simulation and real-world physical experiments. This role offers the unique opportunity to see your research directly accelerate scientific discovery and materials innovation.
Location: London, UK
Why this role is remarkable: You will work at the intersection of frontier AI and physical labs, creating a closed-loop system for autonomous scientific discovery. The company is backed by top-tier VCs and led by world‑renowned experts from elite industry labs and prestigious universities. Your work will have direct real‑world impact by solving fundamental bottlenecks in materials science for EVs, robotics, and clean energy.
What You Will Do:
- Formulate and prototype novel ML architectures like foundation models and GNNs tailored for complex material representations and physics simulations.
- Design active learning and optimization algorithms to autonomously decide which physical experiments the lab should run to maximize discovery.
- Tackle challenges in representation learning using sparse, high-dimensional data generated from real-world physical experiments to sharpen model predictions.
The Ideal Candidate:
- Holds a PhD in Computer Science, Machine Learning, Physics, or a related field with a strong record of publishing novel research.
- Possesses hands‑on expertise in PyTorch or JAX developing modern architectures such as generative models, Bayesian optimization, or foundation models.
- Demonstrates experience applying machine learning to scientific domains or simulations with a deep curiosity for accelerating discovery through autonomous systems.
Machine Learning Research Scientist at well-funded AI materials discovery startup in London employer: Jack & Jill
At Jack & Jill, we pride ourselves on being an exceptional employer that fosters a dynamic and innovative work culture. Our team enjoys a range of benefits including flexible working arrangements, professional development opportunities, and a collaborative environment that encourages creativity and growth. Located in a vibrant area, we offer unique advantages such as access to cutting-edge technology and the chance to work with industry leaders in AI-driven marketing strategies.
