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your suitability with evidence of the following: Have backgrounds in computer science (or engineering), system engineering, or physics/mathematics. Knowledgeable in machine learning techniques (had
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first-class or upper second-class honours degree in mechanical engineering or a related subject. This studentship will attract a stipend of £20,480 for four years. The position arises from an engineering
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The project: As wearable technology becomes increasingly ubiquitous in our lives, it is urgent we better understand how we might use the technology and how the technology can enhance our lives
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methods for nuclear fusion, motivated by yield prediction in tritium fuel cycles. The lack of scalable tools necessitates large engineering tolerances, increasing reactor cost. Empirical tests are expensive
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/people/nc266.html and here https://www.eng.cam.ac.uk/news/engineering-better-car-experience . Four years funding is provided by the UK's Engineering and Physical Sciences Research Council (EPSRC) and JLR
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-on experience with real-world SCADA data, industry collaboration with RES Group, and training in high-fidelity simulation environments (OpenFAST, Digital Twin technology). This opportunity is ideal for those
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for success: A PhD awarded in a relevant discipline e.g. social sciences, history, science and technology studies, anthropology, or other discipline with a strong background in conducting qualitative research
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this testbed available to users for testing hardware and applications. NPL will lead on the testing and security evaluation of the testbed and collaborate widely on the technology development. The student’s
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together leading research groups in the Department of Chemistry, Warwick Manufacturing Group (WMG) and the School of Engineering at the University of Warwick. The centre collectively has world-leading
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additive manufacturing of facial prostheses. Applicants should have, or expect to achieve, at least a 2.1 honours degree or a master's (or international equivalent) in a relevant science or engineering