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profiling Brain slice electrophysiology Human neuropathology Candidate Requirements: We welcome applicants with a background in neuroscience, biomedical sciences, or a related field. Experience with tissue
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research role. We encourage all potential applicants to think about potential proposals for parallel individual projects which may complement these two research projects, and we will work with you to refine
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Specification of the Job Description (available on the university's website, accessed by the 'Apply' button). Any requested additional documents required as part of your application, should be included within
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
complex engineering data and deliver insights that are robust, adaptable, and applicable across complex, high-value, safety-critical domains. This research will contribute to shaping the next generation of
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Honours degree (or equivalent) in an appropriate discipline such as Computer Science or Mathematics. Applicants are expected to have excellent mathematical skills as well as an interest in discrete
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engineering with an emphasis on developing and refining processes which must be compatible with large scale manufacturing. The successful applicants will expect to split their time between the Swansea Bay
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Application deadline: All year round Research theme: Robotics, Smart Manufacturing How to apply:uom.link/pgr-apply-2425 No. of positions: 1 This 3.5 year PhD is funded by the Department
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renewable energy, AI-driven engineering, and industrial research. Cranfield’s expertise in wind energy systems, predictive maintenance, and AI applications provides an ideal environment for cutting-edge
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set of practical short courses delivered in the first year. Applicants should have (or expect to be awarded) an upper 2nd or 1st class honours degree at the level of MSci, MEng (or overseas equivalents
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supportive lab culture with flexible working practices Applications welcome from candidates from under-represented backgrounds Adjustments available to support candidates with physical disabilities