Research Associate in Machine Learning for Protein Design

Location: South Kensington Campus 

About the role: 

Are you interested in developing machine-learning methods for protein design and applying them to a new class of materials-manufacturing problem? The Research Associate in Machine Learning for Protein Design will work on ProteinCAD, the computational protein-design tool of the CADMUS project, led by Dr James W. Murray at Imperial College London.

CADMUS (Computer Aided Design of Materials for Universal Synthesis) is an ambitious UK research consortium from Imperial College London, the University of Sheffield and Change Bio, funded through the UK’s Advanced Research + Invention Agency’s (ARIA) Universal Fabricators programme (https://aria.org.uk/opportunity-spaces/manufacturing-abundance/universal-fabricators). 

The project has a bold goal: to develop a new way of manufacturing advanced magnetic materials by using designed proteins as programmable scaffolds to organise inorganic particles with nanoscale precision.

This job is part of an Advanced Research + Invention Agency-funded project, subject to contract negotiations.

What you would be doing: 

You will develop and apply machine-learning and structural-bioinformatics methods for protein design, with a particular focus on modern generative approaches such as protein diffusion models, flow-based models and related methods. Your work will contribute to ProteinCAD, a computational design framework for creating protein structures with specified shapes, interfaces and assembly properties. 

What we are looking for: 

We are looking for a motivated and collaborative researcher with a strong background in machine learning, structural bioinformatics or computational protein design. In particular, you will have:

• A PhD, or near completion of a PhD, in machine learning, structural bioinformatics, computational biology, computer science or a closely related discipline.
• Experience applying machine learning to protein structure, protein design or a related molecular problem.
• Strong Python skills and experience with a modern deep-learning framework.
• Knowledge of protein structure, protein-design principles and structural bioinformatics.
• An interest in generative protein design, ideally with experience of diffusion, flow-matching or related models.
• The ability to deliver rigorous, reproducible research in a collaborative, milestone-driven environment and communicate findings clearly across disciplines.

What we can offer you: 

• The opportunity to undertake high-risk, high-reward research and help build ProteinCAD within an ARIA-funded programme.
• Close collaboration with computational and experimental researchers across protein design, engineering biology and materials science.
• Access to Imperial’s computational environment, including HPC clusters, cloud computing and agentic GitHub Copilot tools.
• Support to develop an independent research profile through publications, conferences, training and future research proposals.
• Imperial’s career-development support, employment benefits and inclusive research culture.

Further Information

Please note interviews will be held on a rolling basis while the advert is live. It is therefore strongly recommended that you submit your application as early as possible. The advert will be closed once a suitable candidate is selected.

The post will be based in the Department of Life Sciences on the South Kensington Campus, with collaborators at Change Bio (London), and University of Sheffield.

We welcome applications from candidates who do not meet every desirable criterion but have relevant expertise and a strong interest in developing new skills.

The post is full time and fixed term for 18 months, with the possibility of extension.

If you require any further details about the role, please contact: Dr. James Murray – j.w.murray@imperial.ac.uk

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