University Of Strathclyde
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Postdoctoral Research Associate in Machine Learning for Protein Assembly Design University of Strathclyde in United Kingdom
Degree Level
Postdoc
Field of study
Computer Science
Funding
Full-time fixed-term Research Associate post for 18 months, funded by the ARIA-funded CoreShell Fibre Foundry programme. Salary is £39,906 - £46,049. Continuation beyond the initial funded period depends on milestone gate success, further funding, and University approval.
Deadline
Sep 25, 2026
Country
United Kingdom
University
University Of Strathclyde
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About this position
Postdoctoral Research Associate opportunity in machine learning for protein assembly design at the University of Strathclyde. The role sits in the Department of Pure and Applied Chemistry and is part of the ARIA-funded CoreShell Fibre Foundry programme.
The project focuses on developing a new approach to manufacturing hollow inorganic fibres using engineered proteins as reusable molecular fabrication units. The successful candidate will lead the machine-learning component of the computational work package, building predictive and active-learning methods to guide the design of protein sequences that assemble into controlled geometries.
Key research themes include computational chemistry, protein assembly, molecular modelling, bioinformatics, materials informatics, and machine learning. The postholder will build surrogate models linking protein sequence and molecular-simulation descriptors to experimentally observed assembly outcomes, then use those models to prioritise candidate sequences for simulation and experimental testing.
Responsibilities include developing robust Python workflows, analysing sequence/simulation/experimental datasets, defining molecular descriptors and prediction targets, supporting iterative design-build-test cycles, and communicating results to computational and experimental collaborators. The work is interdisciplinary and collaborative, involving computational chemists, protein scientists, and engineers.
Applicants must hold a PhD in a relevant area such as computational chemistry, chemical physics, molecular modelling, bioinformatics, machine learning, computational biology, or materials informatics. Strong Python and scientific-computing skills are required, along with experience developing and evaluating machine-learning models. Experience in active learning, Bayesian optimisation, uncertainty quantification, surrogate modelling, protein or peptide design, molecular descriptors, sequence-based modelling, or molecular dynamics data would be advantageous.
The post is full time and fixed term for 18 months, with a salary of £39,906 - £46,049. The closing date is 25 September 2026. Informal enquiries may be directed to Professor Tell Tuttle at [email protected].
Funding details
Full-time fixed-term Research Associate post for 18 months, funded by the ARIA-funded CoreShell Fibre Foundry programme. Salary is £39,906 - £46,049. Continuation beyond the initial funded period depends on milestone gate success, further funding, and University approval.
What's required
A PhD in computational chemistry, chemical physics, molecular modelling, bioinformatics, machine learning, computational biology, materials informatics or a closely related discipline is required. Applicants should have experience developing and evaluating machine-learning models, strong Python and scientific-computing skills, and the ability to work independently and collaboratively. Experience with active learning, Bayesian optimisation, uncertainty quantification, surrogate modelling, protein or peptide design, molecular descriptors, sequence-based modelling or molecular dynamics data would be advantageous.
How to apply
Use the vacancy page to access the full details and application process. Submit an application before the closing date of 25 September 2026. Informal enquiries can be sent to Professor Tell Tuttle at [email protected].
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