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have an opening for a Senior Digital Learning Designer (SDLD) in our innovative Digital Learning Team, supporting the College of Arts, Technology and Environment (CATE). As a team, we are committed
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EPSRC ReNU+ CDT PhD Studentship: Physics-informed machine learning for deep geothermal systems under uncertainty. Award Summary 100% fees covered, and a minimum tax-free annual living allowance
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part-time positions are available for those committed to application-oriented education. Job Responsibilities Teach and assess at least 3 courses in the following core subjects: Data Analytics & Machine
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within physically sensible design spaces avoiding the need to learn every pathological flow scenario and making machine learning both efficient and reliable. The ultimate goal is to retain the fidelity and
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) for engineered microbial strains. Design and implement machine learning algorithms to predict strain performance and optimise metabolic pathways. Integrate multi-omics datasets into computational workflows
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candidate will: Develop genome-scale metabolic models (GEMs) for engineered microbial strains. Design and implement machine learning algorithms to predict strain performance and optimise metabolic pathways
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machine learning model to rule out heart attacks in the emergency room, which has the potential to translate to large savings for healthcare systems in the world, (2) a computational modelling to assist in
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development, machine learning and signal processing, and system integration. We are interested in working on different areas to improve the BCI technology. These areas include (but are not limited
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About the role We are looking for a Learning Technologist to join our established digital education team to support the Faculty of Medicine with the configuration of relevant learning technology
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Learning and Teaching Administrator ( Job Number: 26000196) Department of English Studies Grade 4: - £25,844 to £26,663 per annum (pro rata) Open-Ended/Permanent - Part Time Contract Duration: N/A