Senior Computational Chemist

Senior Computational Scientist – Drug Discovery

Location:

Cambridge / Paris / Remote (EU/UK)

Team:
Computational Chemistry / AI Drug Discovery

We’re a drug discovery biotech using computational science and AI to design better medicines, faster. Our work directly supports active drug discovery programs, and computational insights are part of everyday decision-making.

We’re at a stage where our platform is proven, our pipeline is moving, and we’re now looking to strengthen senior scientific ownership across programs.

We’re hiring a Senior Computational Scientist to play a leading role in our drug discovery efforts.

You’ll take ownership of computational strategy across one or more programs, working closely with medicinal chemists, biologists, and ML scientists. This role is about influence as much as execution, helping teams decide what to prioritise, what to trust, and where computation adds the most value.

You won’t be managing people on day one (unless that’s your strength), but you will be expected to lead scientifically and set a high bar for quality and thinking.

• Owning and shaping the computational approach within active drug discovery programs
• Designing and interpreting docking, MD, and free energy calculations to guide compound decisions
• Advising teams on the strengths and limitations of different modelling approaches
• Working closely with ML scientists to combine physics-based and AI-driven methods
• Reviewing and improving computational workflows and best practices
• Communicating results clearly and confidently in project and leadership meetings
• Mentoring more junior scientists and helping raise the overall bar

• A PhD (or equivalent industry experience) in computational chemistry, biophysics, physics, or a related field
• Several years of hands‑on experience applying computational methods in drug discovery
• Strong intuition for structure–activity relationships and molecular interactions
• Experience with industry‑standard modelling tools (e.g. Schrödinger, OpenMM, GROMACS, AMBER)
• Solid Python skills for analysis, automation, and reproducibility
• Confidence engaging with experimental teams and influencing decisions

• Deep experience with free energy methods
• Exposure to AI / ML approaches in molecular design
• Experience supporting programs through hit‑to‑lead or lead optimisation in industry

• You’ll have real scientific ownership and visibility across the organisation
• Computation is treated as a strategic capability, not a service function
• Strong collaboration with experimental teams and external partners
• Competitive salary, meaningful equity, and flexible working
• Clear pathways toward principal scientist or broader technical leadership roles