We are an early‑stage scientific software company building a computational platform for modeling chemical reactivity in complex molecular systems. By combining quantum chemistry, machine learning, and molecular simulation, we help scientists understand and predict molecular behavior that drives performance, with early applications in therapeutics, radiopharmaceuticals, catalysis, and related chemistry‑intensive fields.
The Role
As a Computational Chemistry / Molecular Simulation Engineer, you will build and deploy ML/QM simulation workflows for modeling chemical reactivity. You will work across molecular dynamics, quantum chemistry, machine‑learned interatomic potentials, scientific software engineering, and external scientific partner projects.
This role is well suited to a recent PhD, postdoctoral researcher, or equivalent technical contributor who wants to move quickly in an early‑stage startup environment. You should be comfortable with ambiguity, independent execution, and building useful systems rather than only running isolated research calculations.
What You Will Do
- Build data pipelines for DFT, QM/MM, and molecular simulation training data.
- Fine‑tune MACE or related machine‑learned interatomic potential models.
- Run validation against reference QM, DFT, and QM/MM data.
- Develop reproducible molecular simulation workflows for reactive chemistry problems.
- Package computational workflows for external scientific partner projects.
- Integrate simulation pipelines with cloud and HPC infrastructure.
- Translate scientific problems into reliable computational workflows.
- Write clear documentation and maintain production‑quality scientific code.
What We Are Looking For
We are looking for candidates with strong experience in one or more of the following areas:
- Computational chemistry
- Computational biophysics
- Machine learning for atomistic simulation
- Scientific software engineering
- High‑performance computing
- Drug discovery or molecular design
A PhD in a relevant field is preferred, but equivalent technical experience will also be considered.
Required Skills
- Strong Python programming skills.
- Experience with molecular simulation or molecular dynamics.
- Familiarity with quantum chemistry, DFT, or QM/MM methods.
- Experience with machine learning for atomistic systems, neural network potentials, or related approaches.
- Comfort working in Linux, HPC, or cloud computing environments.
- Ability to write reliable, maintainable scientific software.
- Clear communication skills across scientific and engineering teams.
Useful Experience
- MACE, NequIP, Allegro, SchNet, ANI, Orb, or related MLIP frameworks.
- ORCA, Gaussian, Q‑Chem, CP2K, VASP, NWChem, or related QM/DFT packages.
- NAMD, GROMACS, AMBER, OpenMM, LAMMPS, or related molecular simulation software.
- Active learning, dataset curation, or high‑throughput simulation workflows.
- Cloud infrastructure, workflow orchestration, containerization, or scientific DevOps.
- Therapeutics, radiopharmaceuticals, metal‑ligand chemistry, covalent inhibitors, catalysis, or materials chemistry.
Working Style
- Writes production‑quality scientific code.
- Communicates clearly with scientists, engineers, and external partners.
- Can move between theory, code, simulations, and practical scientific problems.
- Works independently while contributing to a small, fast‑moving technical team.
- Values validation, reproducibility, and practical deployment.
- Is comfortable with the speed, ambiguity, and ownership expected in an early‑stage startup.
Location and Employment Type
This is a full‑time role. Candidates should be UK‑based, with a preference for those who can work from Oxford or London. Candidates must have or be eligible to obtain the right to work in the UK.
Compensation
The compensation package will include salary and eligibility to participate in the company’s employee option pool. Final compensation will depend on experience and role scope.
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