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optimisation or machine learning (e.g., Python/Matlab/C++; PyTorch/TensorFlow). Experience in signal processing/wireless or SDR/GPU prototyping is a plus. Demonstrated research potential is highly desirable
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behaviour through these models using uncertainty quantification/machine-learning (UQ/ML) algorithms To optimise the manufacturing process with the help of the simulation tool To support in the development and
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to have a proactive attitude towards problem solving independently. The student is expected that she/he has prior experience using machine learning tools before and be familiar with signal processing tools
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Can We Teach AI to Outsmart Humans in the Werewolf Game—Without Changing the AI Itself? Large Language Models (LLMs) have dazzled us with their ability to converse, code, and create—but they still
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Imaging of Materials Facility (AIM ) led by Professor Richard Johnston and Swansea University's Simulation and Immersive Learning Centre (SUSIM ). The student will develop novel medically bespoke protocols
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successful courses or projects) Be proficient in programming (preferably in Python ot Matlab). Ideally familiar with machine/deep learning, signal processing, dynamical system or mathematical modelling To find
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electrochemical processes (h-index 23, i10-index 43). This studentship is supported through collaboration with leading partners in precision manufacturing sectors such as the company LoadPoint Ltd. Successful
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How to apply: uom.link/pgr-apply-2425 This 3.5-year PhD project is fully funded for home students or EU students with settled status; the successful candidate will receive a tax-free stipend set at the UKRI rate (£20,780 for 2025/26) and tuition fees will be paid. We expect the stipend to...
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including predictive modelling, computer vision and epidemiology. The student will join an established team of investigators, including statisticians, epidemiologists, image scientists, and clinicians
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Aviation by 2050. This exciting doctoral project, in collaboration with Rolls-Royce, will develop innovative computer vision methods which when combined with optical flow velocimetry will enable imaging