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Field
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Research Associate specialising in statistical modelling and machine learning to join our multi-university multi-disciplinary team developing a groundbreaking technique based on autofluorescence (AF) imaging
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people to co-produce research and outputs. About You You will have or be close to the completion of PhD/DPhil/DClin or other professional doctorate degree, together with relevant experience and sufficient
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educators, to give young children a voice. About You You will have or be close to the completion of PhD/DPhil/DClin or other professional doctorate degree, together with relevant experience and sufficient
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) information-theoretic active learning, and c) capturing uncertainty in deep learning models (including large language models). The successful postholder will hold or be close to the completion of a PhD/DPhil in
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. You will write research articles and present the results at national and international conferences. It is essential that you hold a PhD/DPhil in computational biology, genomics, bioinformatics
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Stanford University / SLAC National Accelerator Laboratory | Menlo Park, California | United States | about 23 hours ago
requires a PhD in experimental nuclear physics, particle physics, or a related field at the time of appointment. The successful candidate should have a demonstrated record of excellence in research, and
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. About You The successful applicant will have, or soon obtain, a PhD degree in mathematics or related, or equivalent level of professional qualifications and experience, with expertise in at least one of
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work direction, delegation and establishing priorities. Knowledge – Skills – Abilities Required knowledge: biology, chemistry, statistics, documentation, records management, data utilization, complex
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including training and development as well as daily work direction, delegation and establishing priorities. Knowledge – Skills – Abilities Required knowledge: biology, chemistry, statistics, documentation
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also have or be close to completing a PhD in any of the following areas as well as the will and commitment to learn relevant topics from the other areas: Statistical and machine learning, mathematical