Research Assistant in Analysing and Visualising Neural Perturbome in City of London

The School of Neuroscience is the UK’s 2nd largest Neuroscience school with over 500 researchers and 200 PhD students. It is one of three schools at the Institute of Psychiatry, Psychology & Neuroscience. CDN is one of four departments in the School of Neuroscience at the Institute of Psychiatry, Psychology & Neuroscience and is located at Guy’s campus. Researchers have access to support facilities in genotyping, molecular biology and Drosophila work. CDN has a close partnership with the Medical Research Council (MRC) and CDN researchers, together with clinical researchers from King’s, make up the MRC Centre for Neurodevelopmental Disorders.

At the Centre for Developmental Neurobiology (CDN), we investigate the mechanisms governing the formation of the brain during embryonic development and in early postnatal life. This is based on the understanding that early experience shapes the way our brain is constructed. While the “ground plan” of the brain is genetically determined, it is also influenced by environmental experience. We are still far from a complete understanding of how these processes work.

We are seeking a motivated research assistant to join our team working on an exciting Wellcome Trust-funded project. The research focuses on analysing and visualising neuronal perturbomes, exploring how neural circuits respond when specific neurons or connections are perturbed. In this role, you will contribute to developing computational models of neural circuitry across different architectures and scales. You will simulate how these networks respond to targeted perturbations, then analyse and visualise the resulting patterns to uncover fundamental principles of neural circuit organization and function. This work bridges computational neuroscience, systems biology, and data visualization, offering the opportunity to work on questions at the forefront of neuroscience research.

What you would be doing:

• Developing and implementing neural network models: You will build computational models representing neural circuits with varying architectures, incorporating empirical constraints from connectomic and physiological data. This includes designing simulations to probe how networks respond to systematic perturbations of individual neurons or connections.
• Simulating and analysing perturbation responses: You will run large-scale simulations to generate perturbation datasets, then apply statistical and machine learning techniques to analyse how network activity changes in response to these perturbations. This involves identifying patterns, dependencies, and emergent properties across different conditions and network types.
• Visualising complex neural data: You will create sophisticated visualisations of high-dimensional neural network data and perturbation responses, translating complex computational results into intuitive graphical representations that reveal biological insights and support publication and presentation.

What we’re looking for:

• You should have solid previous experience in visualising, simulating, and analysing large-scale neural networks.
• Familiarity with sparse network architectures is particularly valuable, as many biological neural circuits are sparsely connected.
• Experience building or working with models across different species would be especially beneficial, as this reflects the diversity of neural systems we aim to understand.
• Strong computational skills are essential, along with experience in scientific programming (Python, MATLAB, or similar), data analysis, and visualisation tools.
• Above all, we seek someone motivated by fundamental questions in neuroscience and capable of working independently while collaborating effectively within our research team.

This is a full-time position on a fixed-term contract until 30th November 2026.

About you:

To be successful in this role, we are looking for candidates to have the following skills and experience:

• Master’s in Neuroscience, Physics, Computer Science, or a related field
• Strong computational skills and experience in scientific programming (Python, MATLAB, or similar languages)
• Previous experience simulating neural networks and analysing their responses
• Knowledge of neural network architectures and principles
• Excellent data analysis capabilities
• Experience with visualization tools and techniques for complex, high-dimensional data
• Strong written and verbal communication skills for presenting scientific findings
• Experience with designing efficient and optimised models, including hardware acceleration
• Experience across the full software development lifecycle, from initial design through to deployment and maintenance.
• Previous experience working with sparse network architectures
• Experience building or analysing neural network models across different species
• Familiarity with connectomic or physiological datasets
• Experience with machine learning techniques for data analysis
• Knowledge of perturbation analysis methods
• Experience with version control systems (e.g., Git) and collaborative coding practices
• Familiarity with statistical analysis and hypothesis testing in a research context

We pride ourselves on being inclusive and welcoming. We embrace diversity and want everyone to feel that they belong and are connected to others in our community. We are committed to working with our staff and unions on these and other issues, to continue to support our people and to develop a diverse and inclusive culture at King’s.

As part of this commitment to equality, diversity and inclusion and through this appointment process, it is our aim to develop candidate pools that include applicants from all backgrounds and communities. We ask all candidates to submit a copy of their CV, and a supporting statement, detailing how they meet the essential criteria listed in the advert. If we receive a strong field of candidates, we may use the desirable criteria to choose our final shortlist, so please include your evidence against these where possible.

Grade and Salary: £39,076 – £40,733 per annum, including London Weighting Allowance