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to achieve, at least a 2.1 honours degree or a master’s in a relevant science or engineering related discipline. Applicants should have strong background in Machine Learning and Deep Learning. To apply, please
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may also explore embedding these new computational methods into optimisation and machine learning contexts. The new computational techniques developed will be geared towards the following key
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. The successful candidate will develop advanced skills in multi-modal sensor fusion, signal processing, machine learning, and integrity assessment, as well as transferable abilities in critical thinking, project
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Supervisors: Dr Tim Halim and Dr Gregory Hamm Course start: 1st October 2026 Overview The project will be supervised by Dr Tim Halim, Dr Albert Koulman (Institute of Metabolic Science) and Dr Gregory Hamm (AstraZeneca). Project details The tumour immunity cycle involves cyclical trafficking of...
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including machine learning. This research will support the path to net zero flights and there will be opportunities to become involved in practical aspects of fuel system design and testing during their PhD
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This research opportunity invites self-funded PhD candidates to develop advanced deblurring techniques for retinal images using deep learning and variational methods. Retinal images often suffer
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Two fully-funded 3-year PhD studentships are available in Neuromorphic and Bio-inspired computing at the interface between control engineering, electrical engineering, computational neuroscience
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chemistry or analytical chemistry/chemical engineering will be an advantage. The successful applicant would be expected to spend part of the PhD period based in Bristol at the Airbus site and will receive
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Criteria You must have, or expect to gain, a minimum 2:1 Honours degree, or international equivalent, in chemistry, or chemical engineering, or in a closely related field. If you do not meet these entry
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processes associated with CIN [1], leveraging single-cell DNA sequencing understand CIN heterogeneity [2], and development and implementation of machine learning and AI models to imaging data [3]. The student