Research Fellow: AI for Molecular Modelling - 16961

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.

College / Directorate

College of Engineering, Design & Physical Sciences

Department

Department of Computer Science

Full Time / Part Time

Full Time

Posted Date

10/08/2026

Closing Date

21/09/2026

Ref No

5193

• Job Description (Word , 86.75kb)

Position Title: Research Fellow: AI for Molecular Modelling – 16961

Department/College: Computer Sciences / College of Engineering, Design and Physical Sciences

Location: Brunel University of London, Uxbridge Campus

Salary: Grade R1 from: £41,292 to £43,572 per annum inclusive of London Weighting with potential to progress to £48,557 per annum inclusive of London Weighting through sustained exceptional contribution. (Pro-rata for Part-time)

Hours: Full-time

Contract Type: Fixed-term until 30/11/2028

Brunel University of London was established in 1966 and is a leading multidisciplinary research-intensive technology university delivering economic, social and cultural benefits. For more information please visit:

The Department of Computer Science at Brunel, where this project will be based, has a strong record of internationally recognised research. In the 2020–2025 editions of the NTU Performance Ranking of Scientific Papers for World Universities, Computer Science at Brunel was ranked in the top 10 in the UK overall. It was also ranked first in the UK for H-index and highly cited papers for five consecutive years. More recently, Brunel was ranked 48th worldwide for Artificial Intelligence in the 2025 Shanghai Global Ranking of Academic Subjects.

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.

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.

We are looking for a computational scientist with an interest in interdisciplinary research applied to biological and toxicological sciences. 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.

• We offer a generous annual leave package plus discretionary University closure days, excellent training and development opportunities as well as a great occupational pension scheme and a range of health-related support.

The University is committed to a hybrid working approach.

Closing date for applications: 21September 2026

Interviews will take place during the week of 12 October 2026 online.

Basic Disclosure and Barring Service (DBS) check is required for this role.

Brunel University of London wishes to promote an inclusive and diverse workforce and create a culture that values the contribution of all backgrounds and communities. All employees will be recruited, selected and appointed in line with our equality and diversity policy.

#J-18808-Ljbffr