22 programming-"https:"-"https:"-"https:"-"BioData" research jobs at University of Nottingham
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skeletal muscle metabolism and how exercise affects it. The post holder will be responsible for the day-to-day running of this programme of work as part of Prof Tsintzas’ research team in the Division
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working with Johnson Matthey, but aligned with the EPSRC funded Programme Grant “Dialling up performance for on demand manufacturing” (EPSRC reference: EP/W017032/1). Our vision is to create a toolkit and
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. Summary This programme of research builds on our previous studies where we identified genes we believe mediate pain and inflammation in the joints of patients with osteoarthritis. The aim of the current
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skeletal muscle metabolism. The post holder will be responsible for the day-to-day running of this programme of work as part of Prof Tsintzas’ research team in the Division of Physiology, Pharmacology and
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Elena Besley to work on the “Enabling Net Zero and the AI Revolution with Ultra-Low Energy 2D Materials and Devices (NEED2D)” Programme Grant. The NEED2D project funds a team of UK scientists at Queen
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, to deliver the final stages of this multi‑year research programme and support the production of high‑quality scientific outputs. About you- You will bring strong data analysis skills, including
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process simulation, techno-economic analysis (TEA), and life cycle assessment (LCA) methodologies Strong computational skills, including proven expertise in programming environments (e.g., Python, Matlab
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Applications are invited to join an ERC-funded research programme in the laboratory of Dr Vinay Shukla. The position is part of the project BreathingUnderground, which explores how oxygen
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will have specific responsibility for research and for developing research objectives and proposals on behalf of the Digital Cancer Screening Research Group. The role holder will be expected to plan and
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across work packages. You will be expected to plan and conduct your own analyses using available tools, to adapt existing methodologies and models, and design new models that improve our understanding