At a Glance
- Tasks: Develop AI methods for predicting species sensitivity to chemicals using molecular modelling.
- Company: Brunel University, a leading research-intensive technology university.
- Benefits: Competitive salary, generous leave, training opportunities, and a great pension scheme.
- Other info: Hybrid working model and commitment to diversity and inclusion.
- Why this job: Join a groundbreaking project that combines AI with environmental science for real-world impact.
- Qualifications: Experience in protein modelling, docking, machine learning, and Python software development.
The predicted salary is between 41292 - 43572 £ per year.
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
- 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: 21 September 2026. Interviews will take place during the week of 12 October 2026 online. A 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.
Research Fellow: AI for Molecular Modelling - 16961 in Uxbridge employer: Brunel University of London
Brunel University of London is an exceptional employer, offering a dynamic work environment in Uxbridge that fosters academic excellence and innovation. With a strong emphasis on research-driven teaching, employees benefit from generous annual leave, comprehensive training opportunities, and a supportive community that encourages professional growth and collaboration.
Contact Details:
Brunel University of London Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Research Fellow: AI for Molecular Modelling - 16961 in Uxbridge
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We think you need these skills to ace Research Fellow: AI for Molecular Modelling - 16961 in Uxbridge
Some tips for your application 🫡
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How to prepare for a job interview at Brunel University of London
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