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optimisation techniques and AI-based models to support decision-making in microgrid design and operation. Working in collaboration with a leading global mission critical firm of engineers, this project offers
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. • To develop and improve theoretical models of fluid dynamics, solid mechanics, soft matter or active matter. • To carry out analytical calculations in the context of theoretical models of fluid
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implementation of deep learning and computer vision frameworks across a range of research projects. This includes developing and training deep learning models for tasks such as scene understanding, object
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of support for health and wellbeing including discounted membership for our state of the art sport and gym facilities and access to a 24-7 Employee Assistance Programme. • On site nursery is available plus
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/Siemens Simcentre to develop AI-assisted programme and models for powertrains and propulsion systems within the transportation and energy sectors. Skills Demonstrable ability to work cooperatively as part
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: solar magnetic field modelling, computational fluid dynamics, or solar observational data analysis. Working knowledge of at least one scientific computing environment (e.g. Python, Fortran, Matlab, C
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students and over 500 Single Honours undergraduate students. We offer a 3-year BSc degree programme in Biological Sciences and a 4-year MBiol, while also contributing to Natural Sciences. We also run a PGT
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and PhD students. Research spans a wide range. Current interests include: Bayesian statistics; modelling of structure, geometry, and shape; statistical machine learning; computational statistics; high
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for our state of the art sport and gym facilities and access to a 24-7 Employee Assistance Programme. • On site nursery is available plus access to holiday camps for children aged 5-16. • Family
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University Guide 2024, and ranked 4th for impact in REF 2021. Due to the reach and scope of the Contextual Safeguarding programme most team members work to a hybrid working model, with research underway in