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related topic: Strong understanding of power electronics principles Excellent knowledge on data-driven machine learning algorithm and experience in using these algorithm for electrical engineering problems
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Electronic Engineering, Control Engineering, Computer Science or a very closely related topic: Strong understanding of power electronics principles Excellent knowledge on data-driven machine learning algorithm
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We are seeking a highly motivated and skilled Research Associate / Fellow to conduct a programme of research on using flat optical fibre sensors to monitor reinforced concrete structures. This work
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Supervisor: Dr Qian Yang, Dr Rebecca Ford, Prof Ian Fisk Subject Area: Sensory Science Research Title: Understanding sweetness and flavour perception in frozen desserts Research Description: Sweet
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Supervisor: Dr Qian Yang, Dr Rebecca Ford, Prof Ian Fisk Subject Area: Sensory Science Research Title: Understanding sweetness and flavour perception in frozen desserts Research Description: Sweet
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work under the supervision of Prof. Stam Sotiropoulos and Prof. Markus Kaiser and their established teams (https://conilab.nottingham.ac.uk https://www.dynamic-connectome.org/ ) in using brain MRI and
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VR/AR, quantum tech, life-sciences, computing and biomedical imaging. The project will work on cutting-edge optical technologies alongside collaborators Prof Melissa Mather, Prof Dmitri Veprintsev, and
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Supervisors: Prof Ioan Notingher (School of Physics and Astronomy) Dr George Gordon and Dr Abdelkhalick Mohammad (Faculty of Engineering) Funding: fully-funded (stipend and PhD fees) Start date
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We are looking for a researcher, whose expertise lies in Discontinuous Galerkin discretisations, compressible flows, Fortran, Python, to work with Luis Espath & Prof Paul Houston jointly with Space
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performance at interview. Project Description (EngD): EngD on Multi-Stage Simulation of Aerospace Out-of-Autoclave Composite Manufacture sponsored by GKN Aerospace (Supervised by Dr Mikhail Mateev and Prof