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techniques from optimization and control theory, scientific machine learning, and partial differential equations to create a new approach for data-driven analysis of fluid flows. The successful applicant will
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The role will develop new AI methods for identifying the instantaneous state of a fluid flow from partial sensor information. The research will couple techniques from optimization and control theory
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This is a Research Fellow post to support the NIHR funded programmes OPtimal Timing of Induction of labour to improve Maternal and perinatAL outcomes (OPTIMAL): An individual participant data meta
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to deliver industry-relevant tools that enable optimal design and operation of hydrogen technologies in real-world application. The successful candidate will work at the intersection of multi-disciplinary
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/VR applications (e.g., babylon.js, A-Frame, etc.) will be an advantage Experience in developing XR app for teaching & learning/training. Experience developing optimized modules in C#/C++ within Unity
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will then analyse complex patterns of data and derive an optimal set of items to form a smart self-report instrument. This two-year project is fully funded by the Hearing Industry Research Consortium
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the research team to develop solutions for adapting CCS2 chargers for marine electrical vessels and optimizing DC fast charging technology for marine applications. As a Research Engineer (Electrical Engineering
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studies within the hydrogen research hub (HI-ACT) funded by EPSRC. The project seeks to deliver industry-relevant tools that enable optimal design and operation of hydrogen technologies in real-world
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. The research group is seeking a talented Doctoral Researcher in nonlinear systems and control with strong interest in nonlinear stability theory, modeling & identification, optimal control, certifiably safe
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be requested at a later date. This position is offered full time on a fixed term until 31 October 2026 and it is funded by COI Core Funding and the National Institute for Health Research (OPTIMAL Study