Overview

Senior & Principal Applied AI Scientists – Automated Labs & Generative Modelling

Oxford/London | Hybrid | Full-time

• A top quartile salary designed to attract and reward world-class talent, plus comprehensive benefits (private medical, pension, income protection, enhanced holiday).
• Electric car scheme & lifestyle perks.
• A collaborative culture that values curiosity, resilience, and creativity.
• You\'ll be working with a world-class team.

Are you ready to join one of the most ambitious and rapidly scaling AI teams being built in Europe right now?

We’re assembling an elite group of researchers and engineers, drawing talent from FAANG, leading AI scaleups, and cutting-edge academic labs, to tackle some of the biggest scientific challenges of our time.

This is your chance to apply AI and automation at scale to reimagine how discovery happens in materials science, chemistry, and the life sciences.

Why this role matters

• Leveraging generative modelling, robotics, and autonomous experimentation to accelerate breakthroughs in chemistry, biology, and materials.
• Partner with leading scientists, engineers, and technologists from across the globe.
• Contribute to programmes that with strong humanitarian impact.
• Help build automated, data-driven research pipelines that move ideas from concept to solution faster than ever before.

What you’ll do

• Lead and contribute to the design and implementation of AI-driven discovery pipelines.
• Apply deep learning, foundation models, and generative approaches to problems in chemistry, materials, and the biosciences.
• Integrate with automated labs and high-throughput platforms to run closed-loop experiments.
• Collaborate with domain experts to ensure solutions address real scientific needs.
• Mentor and guide other scientists, setting the standard for technical excellence.

What we’re looking for

• PhD (or equivalent) in ML/AI, computational sciences, chemistry, materials, or related fields.
• Proven experience applying state-of-the-art ML models to real-world problems.
• Experience with generative modelling and/or automated laboratory systems.
• Strong track record of working with complex, large-scale scientific data.
• Excellent communication and the ability to work across disciplines.

Nice to have

• Experience in high-impact scientific domains (chemistry, drug discovery, materials, biology).
• Background in start-ups or fast-paced R&D environments.