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Field
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relevance. A digital twin framework for safe, simulation-based validation before deployment in operational wind farms. Develop explainable AI (XAI) frameworks and human-computer interfaces that enable wind
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Applications are invited to undertake a three-year PhD programme in partnership with industry to address key challenges in manufacturing engineering. The successful candidate will be based
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are invited to undertake a three-year PhD programme in partnership with industry to address key challenges in on-platform manufacturing engineering. The successful candidate will be based at the Rolls-Royce
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genetics, and may include expertise in one or more of the following: computational biology, statistical genetics, population genetics, biomedical informatics, complex genetics, clinical genetics
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This self-funded PhD opportunity explores assured multi-sensor localisation in 6G terrestrial and non-terrestrial networks (TN–NTN), combining GNSS positioning, inertial systems, and vision-based sensors to deliver resilient, high-accuracy positioning. The project sits at the intersection of...
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scholarship is suitable for students with a background in Engineering, Mathematics, and Computer Science. Students with interests in machine learning, deep learning, AI, intelligent decision making
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microscopy techniques and image analysis (confocal, multiphoton, or other advanced imaging techniques) and/or electrophysiology. Demonstrated computational knowledge, use of ImageJ, and familiarity with a
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research program focused on spatial immuno-oncology, utilizing cutting-edge technologies (e.g., spatial transcriptomics, spatial proteomics, imaging mass cytometry) to study the tumor microenvironment
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://www.bris.ac.uk/pg-howtoapply . Please select Mechanical Engineering (PhD) on the Programme Choice page. You will be prompted to enter details of the studentship in the Funding and Research Details sections
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Supervisors: Professor Sir Steve Jackson and Dr Mark O'Connor (AZ Partner) Course start date: 1st October 2026 Project details Targeted Alpha Therapy (TAT) selectively delivers high Linear Energy Transfer (LET) alpha-particles to cancer cells, maximising efficacy while minimising toxicity. ...