This position will contribute to the UKRI NERC-funded project “Defining species sensitivities to endocrine-disrupting chemicals” led by Brunel University of London in collaboration with the University of Southampton. The project aims to develop innovative computational approaches to predict which vertebrate species are most sensitive to endocrine-disrupting chemicals and to identify the molecular and structural features underlying differences in sensitivity. It will investigate nine families of nuclear receptors across fish, amphibians, reptiles, birds and mammals.
We are looking for a computational scientist with an interest in interdisciplinary research applied to biological and toxicological sciences.
The Research Fellow will deliver the computational component of the project through protein structure modelling, molecular docking and detailed analysis of protein-ligand interactions. They will integrate these results with receptor-interaction data generated by the experimental collaborators at the University of Southampton to develop and evaluate artificial intelligence (AI) methods for predicting chemical binding and species sensitivity. The postholder will work closely with Brunel project team (Dr Alessandro Pandini and Dr Matloob Khushi) and collaborators at the University of Southampton (Dr Nic Bury and Dr Fernando Calahorro Nunez) to integrate computational and experimental research and disseminate the project’s findings.
The role will advance interdisciplinary research at the interface of AI, computational biology and environmental science, contributing to the research objectives of the Department, College and wider University. The project has the potential to improve understanding of chemical risks across species and support the development of more effective approaches to environmental risk assessment.
Candidates are expected to hold a PhD in Chemistry, Biochemistry, Physics, Biophysics, Computational Biology, Computer Science or a related discipline.
Preference will be given to candidates with knowledge and experience of protein molecular modelling, protein–ligand docking, machine learning methods for computational biology, and software development in Python. For detailed information, please refer to the job description available on the Brunel Vacancy website (Ref No 5193).
For informal general discussion regarding the above post, please contact Dr Alessandro Pandini.
Interviews are expected to be during the week commencing 12th October 2026.
Closing date for applications: 21st September 2026
For full details and how to apply:
careers.brunel.ac.uk/vacancy/research-fellow-ai-for-molecular-modelling-16961-617365.html