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classification. The work will involve analytical studies, computer simulations, and finite element (FE) analysis, alongside experimental development and validation. Entry requirements The minimum entry requirement
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these psychological constructs into formal computational rules suitable for agent-based modelling. The PhD student will ensure that formalisations remain faithful to the underlying psychological theory—a translational
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health professions (please note the PhD stipend is set at standard level and is not intended to match a clinical salary). The PhD is integrated within a new 6 year NIHR programme grant focused on improving
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the ‘Sustainable Transitions – Leverhulme Doctoral Training Programme’ at the University of Essex. Only UK domiciled applicants who meet the following criteria may apply: Not already have a Master’s degree from the
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laboratory experience, such as: DNA/RNA extraction, PCR, cloning, virus production, ELISA, etc. Computational biology laboratory experience, such as: bulk- singl cell- or spatial-transcriptomic data analysis
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observer-based techniques, to enable real-time prediction of internal states and ageing mechanisms. Emphasis will be placed on balancing model fidelity, computational efficiency, and robustness under varying
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note, this opportunity is only available to UK Home students. An annual stipend for up to three years - confirmed amount to be inserted. Access to specialist research facilities, computing infrastructure
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Applications are invited for a Research Associate in Climate Change and Computational Modelling. This is a postdoctoral-level appointment, but applicants within a few months of submitting their PhD
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-performance Olympic programme ahead of Los Angeles 2028 and beyond. Working as an embedded researcher within GB Taekwondo, you will explore current nutrition practice and the views of male and female athletes
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computational fluid dynamics (CFD) simulations of blood flow through arteries and develop a cutting-edge super-resolution framework using convolutional neural networks (CNNs). The ultimate goal is to vastly