An early-stage biotechnology company is looking for a Machine Learning Scientist to help develop advanced simulation models for complex molecular systems.
This is a highly technical, hands-on role at the intersection of:
* Machine learning
* Molecular simulation
* Computational chemistry
The work is applied and experimental-focused, meaning your models will directly inform real-world lab decisions rather than purely theoretical outputs.
You’ll join a small, collaborative team combining computational and experimental expertise, with the opportunity to take real ownership over model development and direction.
What You’ll Be Doing
* Developing and refining machine learning models for molecular systems
* Running and analysing molecular simulations (MD / QM / DFT)
* Building and optimising custom force fields / learned potentials
* Benchmarking and improving model accuracy
* Scaling workflows using HPC / GPU systems
* Working closely with experimental teams to guide testing and validation
* Contributing to new methods, datasets, and IP development
What They’re Looking For
* Strong background in computational chemistry / molecular simulation
* Experience with:
* Quantum chemistry / DFT / ab initio methods
* Exposure to machine learning applied to scientific or physical systems
* Comfortable working in a research-driven, technical environment
* Experience with:
* Force fields / potential models
* Complex materials or coordination chemistry
* Experience using tools such as:
* Exposure to HPC / GPU environments
* Background in early-stage or research-led environments
Background
* PhD in Computational Chemistry, Physics, Materials Science, or similar
* or
* MSc with strong relevant research or industry experience
Why Apply?
* Work on a highly novel problem space combining AI + chemistry
* Direct impact on real-world experimental outcomes
* High level of ownership and technical freedom
* Early-stage environment with strong growth potential
* Reduced working hours (32-hour week) supporting work-life balance
Who This Suits
This role is ideal for someone who:
* Enjoys deep technical problem-solving
* Wants to bridge research and real-world application
* Is motivated by ownership and impact rather than pure production work
Please note: due to the highly technical nature of this role, candidates should have demonstrable experience in molecular simulation and machine learning within a scientific context.
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