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Full-time: 35 hours per week Open-ended (permanent)/Fixed term: 31 August 2026 The project is looking to recruit research assistant(s) familiar in AI, NLP and financial computing to assist with
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engineering, or atmospheric science* Expertise in and passion for computational modelling and software development/engineering Expertise in cloud physics or contrails preferred but not required Creative problem
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Programme (NSIP). The position is full-time and fixed-term until 31 March 2027. This interdisciplinary project is conducted in collaboration with the Department of Plant Sciences and other industry partners
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High Performance Computing facility, where the current code is implemented. The candidate will, among other activities, extend the model to treat different management interventions, peat growth and decay
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patient samples. The Sheffield arm of the project will develop statistical and machine learning models to identify and validate predictive biomarkers of resistance evolution in Pseudomonas aeruginosa lung
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27 Sep 2025 Job Information Organisation/Company University of Nottingham Research Field Computer science » Other Engineering » Biomedical engineering Medical sciences » Other Researcher Profile
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, policymakers, and charities interested in using economic policies to improve people's health. Taking a systems science approach, the HealthMod consortium develops public health computational modelling
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of quantitative analysis and statistical modelling to support the project’s aims of assessing the contribution of An. stephensi to malaria transmission relative to native malaria vectors across a range of
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We are seeking a research assistant with a background in computing to develop AI models for image reconstruction from data from our ultra-thin fibre-based spatial frequency domain imaging device
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to/ lead the development and implementation of quantitative analysis and statistical modelling to support the project’s aims of assessing the contribution of An. stephensi to malaria transmission relative