Summary
The Department of Pure and Applied Chemistry is seeking an exceptional and highly motivated Research Associate to join the ARIA-funded CoreShell Fibre Foundry programme. This programme aims to develop 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, developing predictive and active-learning approaches to guide the design of protein sequences that assemble into controlled geometries.
Designation
Postdoctoral Research Associate (PDRA)
Research Area
- Machine Learning for Protein Assembly Design
- Computational Chemistry
- Chemical Physics
- Molecular Modelling
- Bioinformatics
- Materials Informatics
Location
University of Strathclyde, Department of Pure and Applied Chemistry
Eligibility/Qualification
Required:
- A PhD in computational chemistry, chemical physics, molecular modelling, bioinformatics, machine learning, computational biology, materials informatics, or a closely related discipline.
- Experience developing and evaluating machine-learning models.
- Strong Python and scientific-computing skills.
- Ability to work both independently and as part of a collaborative research team.
Advantageous:
- Experience with active learning.
- Bayesian optimisation.
- Uncertainty quantification.
- Surrogate modelling.
- Protein or peptide design.
- Molecular descriptors.
- Sequence-based modelling.
- Molecular dynamics data.
Job Description
Working within an interdisciplinary team of computational chemists, protein scientists, and engineers, you will:
- Develop machine-learning and active-learning models for predictive protein-assembly design.
- Define suitable molecular descriptors, input features, and prediction targets.
- Analyse sequence, simulation, and experimental datasets.
- Prioritise candidate protein sequences for simulation and experimental validation.
- Develop robust, documented, and reproducible Python workflows.
- Communicate model outputs clearly to computational and experimental collaborators.
- Contribute to project meetings, milestone reports, publications, presentations, and research-data management.
How to Apply
Informal enquiries may be directed to Professor Tell Tuttle, Programme Lead, at tell.tuttle@strath.ac.uk. To apply, please use the provided application link.
Last Date for Apply
25 September 2026
