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Research Group: Nanocomposites Project Overview We welcome a highly motivated PhD researcher with a background in chemistry, polymer science, materials science, chemical engineering, or a related discipline
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backgrounds such as AI, computer vision, computer graphics, machine learning, robotics, wearable technologies, textile engineering, fashion technology, digital fashion, or related areas are encouraged to apply
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This 3.5-year PhD project is fully funded by The Department of Mechanical and Aerospace Engineering; students who are eligible to pay tuition fees at the Home rate are eligible to apply
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background in semiconductor physics or engineering. If you are interested in this exciting opportunity, we invite you to apply online at: https://www.sheffield.ac.uk/eee/phd Funding Notes Only available
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an enthusiastic PhD candidate to help enable the circular economy for plastics within the automotive industry. Working with industry co-sponsor Artifex (https://www.artifexinteriorsystems.com ) and based in
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motivated students with a strong background in engineering or computer science. The ideal candidate will have: Strong programming and software skills. An awareness of machine learning theory and techniques
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, Physics, Computer Science, or a closely related discipline. The ideal candidate will have: A strong background in radar, microwave engineering, signal processing, electromagnetics, machine learning
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or Python). Knowledge of the social identity approach and health psychology models are essential, and experience of network science or computational modelling is desirable.
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of the trypanosome intraflagellar transport (IFT) motors and determine how their architecture supports flagellum assembly and function. You will apply multi-disciplinary approaches from cell biology, parasite genetics
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laboratory environment with some statistical methodology is desirable. How to apply Applications should be submitted via the Veterinary Medicine and Science PhD programme page. In place of a research proposal