Research Associate or Senior Research Associate (computational modelling of renal nephrotoxicity)

Location: Hammersmith Campus

About the role:

This is an exciting opportunity to join the GSK–Oxford–Imperial Modelling-Informed Medicine Centre (MiMeC) and develop computational and mechanistic models of oligonucleotide-induced nephrotoxicity. This is a unique opportunity for an ambitious researcher to work at the interface of computational physiology, systems biology, and toxicology, developing models that translate experimental and clinical data into mechanistic insight and predictive tools for renal safety assessment.

This post is funded by GlaxoSmithKline Research and Development Ltd (GSK) and will form part of the MiMeC Renal Theme, focused on building quantitative frameworks to improve understanding and prediction of renal injury and function.

You will work within Professor Steven Niederer’s computational physiology group at Imperial College London’s National Heart and Lung Institute, collaborating closely with scientists and clinicians from Imperial, Oxford, and GSK. The role offers opportunities to combine physiological modelling, AI-assisted data integration, and simulation to build model-informed drug safety and efficacy tools relevant to both preclinical and clinical applications.

What we are looking for:

• A PhD and equivalent experience in Biomedical Engineering, Computational Physiology, Systems Biology, or a related quantitative discipline.
• Experience in mechanistic or multi-scale modelling of biological or physiological systems.
• Knowledge of renal physiology, toxicology, or related organ-level disease processes.
• Strong computational and analytical skills, with proficiency in Python or Julia.
• Experience in statistical modelling, parameter estimation, or uncertainty quantification (e.g. Bayesian inference or global sensitivity analysis).
• Interest in translational safety or pharmacology modelling, and a willingness to engage with industrial and academic collaborators.
• Excellent communication skills and a strong publication record.

Desirable:

• Experience integrating experimental, omics, or clinical datasets into quantitative models.
• Familiarity with AI/ML methods for model calibration, emulation, or data-driven discovery.
• Prior experience in open-source software development and collaborative codebases (e.g. GitHub).

What you would be doing

• Developing and applying multiscale computational models to describe mechanisms of oligonucleotide-induced nephrotoxicity.
• Integrating in vitro, in vivo, and clinical data to link molecular and cellular mechanisms to kidney-level injury and adaptation.
• Applying statistical and AI-based methods for model calibration, validation, and uncertainty quantification.
• Working closely with GSK and Oxford collaborators to align model outputs with preclinical and clinical safety questions.
• Delivering open-source tools, reproducible code, and high-quality publications.
• Presenting findings to Imperial, Oxford, and GSK stakeholders and contributing to collaborative project planning.
• Participating in potential short secondments at GSK to test models on industrial datasets and support decision-making.

What we can offer you:

• Supporting you in developing your career into an independent researcher at a world-leading institution
• Working with the Cardiac Electro-Mechanics Research Group led by Prof. Steven Niederer
• Sector-leading salary and remuneration package (including 39 days off a year)

Further Information

The is a full time, fixed term role for 3 years with the possibility of an extension.

Please indicate in your supporting statement which job description best aligns with your background and expertise. Candidates will be considered for the appropriate level of seniority based on their experience and qualifications.

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