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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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with support from biostatisticians within the group. The bioinformatic work will be performed using high performance cloud computing solutions. This project offers the opportunity to utilise emerging
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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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states and ageing mechanisms. Emphasis will be placed on balancing model fidelity, computational efficiency, and robustness under varying operating conditions. The outcomes will support next-generation BMS
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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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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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examine similar unorthodox approaches to health in the 20th and/or 21st Century are encouraged. While we encourage candidates to design their own programme of research, possible foci for the PhD studentship
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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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) and electrochemistry (Prof. Tanja Kallio, Prof. Daniel Martin-Yerga, and Prof. Pekka Peljo). The department also has strong research activities in simulation and computation as well functional materials