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research thrusts within Wu laboratory’s overall programme. We are looking for a researcher with a PhD in engineering, or a related physical science discipline who has prior experience and possess a deep
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year-long module performance in the water industry; (ii) exploring whether machine learning, couple with transport informed models can be used to predict membrane fouling for specific applications
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folding. The ability to rapidly learn new techniques is highly desirable, and enthusiasm for working across disciplinary boundaries is essential. Full training will be provided where needed. Prior
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of the Fellowship, including its bespoke training and mentoring programme, leads to the opportunity for a permanent academic appointment from September 2029. Join Our Live Webinar Learn more about the Fellowships
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establishing yourself in the field. Candidate Profile: A PhD in Power Electronics is desirable or a minimum Masters level qualification with some industry experience (both in power electronics). Skills
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collaboratively to develop engaging modules, integrate Autodesk tools across the curriculum, and create learning experiences that empower students to thrive in a rapidly evolving engineering landscape. As part of
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are looking for a researcher with a PhD (or near completion) in engineering, data science, computational social science or a related discipline, with experience in data analytics, NLP or machine learning. You
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: Minimum MSc degree in Civil Engineering or Material Science applied to construction materials with minimum two years of industry experience. A PhD would be desirable. Skills/experience required include
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control health and disease. Candidate Profile: MSc or above in cell biology, immunology. PhD graduates are preferred for their direct experience with immunology and specialised equipment, however MSc or
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. Understanding of GDPR and Data Collection policies. Strong numerical and analytical skills. Understanding of ethical issues and approvals. Desirable for the role: PhD in a relevant discipline or an equivalent