Research Scientist, Computational Chemistry & Molecular Simulation

The role

We are building AI systems that can carry out scientific research. You will use computational chemistry and molecular simulation to answer concrete questions in industrial R&D, such as how molecules bind, which structures are stable, or how a reaction proceeds. Potential applications include drug discovery and materials science.

Working alongside our Head of Scientific Applications, founders, and engineers, you will turn research objectives into computational studies and carry them through to useful results. You will choose methods, write code, run calculations, and determine whether the evidence supports a scientific decision.

You will work with established scientific software and, where useful, our own models. The workflows and evaluations you develop will help our agents perform scientific work with increasing autonomy.

What you will do

• Design studies of molecular interactions, binding, stability, or reaction energetics, with appropriate approximations, baselines, and success criteria.
• Prepare molecular systems and implement calculations using molecular dynamics, free-energy methods, or electronic structure, as appropriate to the problem.
• Diagnose failures involving structures, force fields, electronic states, sampling, convergence, or the limitations of the chosen method.
• Compare predictions with experimental measurements or credible reference calculations, assess uncertainty, and recommend what to investigate next.
• Build reproducible workflows for system preparation, calculation setup, and analysis, and communicate findings and limitations to colleagues and customers.
• Work with engineers to turn validated protocols into tools for our agents, including evaluations and checks that detect unreliable results.

What we are looking for

You should be able to independently own a well-defined computational study and exercise good judgment about the reliability and usefulness of its results.

Strong candidates will bring:

• Deep practical expertise in at least one of molecular dynamics, free-energy calculations, electronic structure, or atomistic materials modelling.
• Strong scientific Python skills and experience personally implementing, modifying, and troubleshooting calculations.
• Experience with scientific software such as OpenMM, GROMACS, PySCF, ASE, or comparable tools relevant to your area.
• A record of choosing appropriate methods, understanding their limitations, and validating computational results against credible evidence.

A PhD in computational chemistry, physics, materials science, or a related field is valuable; equivalent research experience also counts. Industry experience and familiarity with scientific machine learning or AI agents are useful but not required.