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Field
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PhD (or be near completion) in a field such as AI, computer science, signal processing, biomedical engineering, have a strong record of publication in engineering or computer science literature, and
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of the project. Applicants should hold, or be close to completion of, PhD/DPhil in Biology or a related subject. You should have a high level of competence in cell biology and relevant experience demonstrated by
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), to develop systems that improve the efficacy of machine learning-based technologies for healthcare applications. You must hold a PhD (or be near completion) in a field such as AI, computer science, signal
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for more information. About you To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria PhD qualified in relevant subject area from a
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successful in this role, we are looking for candidates to have the following skills & experience: Essential criteria PhD qualified in relevant subject area* Experience developing deep learning segmentation
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must hold a PhD in psychology, animal behaviour, or another related field and must show experience with having worked with animals, ideally birds (and preferentially corvids). The applicant must have
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of migration in cetaceans’. The post holder will provide guidance to less experienced members of the research group, including research assistants, technicians, and PhD and project students. The post holder will
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quality refereed journals and write reports for submission to research sponsors. You must hold a PhD (or be near completion) in a biomedical field of laboratory-based research (ideally immunology and/or
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for differential rate correction). The successful applicant will hold, or be close to completion of, a relevant PhD/DPhil in bioinformatics, comparative genomics and phylogenetics, together with relevant experience
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have completed, or be close to completing, a PhD/DPhil in a relevant quantitative field such as computational social science, computer science, or cognitive science. They will have a demonstrable track