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industry interact. We are recruiting up to five scientists with an interest in functional genomics to join the FGSL screening team. For this role (PR41799) we will be considering candidates without a PhD
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platforms will be designed, capable of efficiently exploring complex mixed variable design spaces on the microlitre scale. Our multisite reactor network will be driven by next generation machine learning
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be part of a small team, led by Dr Susanne Bornelöv, which studies gene regulation using various approaches including machine learning, evolutionary genomics, and sequencing bioinformatics. Our team is
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candidate will have a PhD in a strongly quantitative discipline, but applications from candidates close to submitting their PhD are also welcome. Familiarity with deep learning methodologies is essential, as
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learning and AI, and all other areas of academic scholarship as may be generally considered as applied mathematical analysis, to take up appointment as soon as possible. Candidates will have an outstanding
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an outstanding record of promoting the public understanding of mathematics in diverse ways. Candidates should hold a PhD or equivalent and be able to demonstrate a strong record in research in
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than 2 years postdoctoral experience. Those with less experience or are about to submit their PhD should apply for role (PR41799). You will be applying your biological expertise in complex cell models
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applicant will have completed (or be about to complete) a PhD in Chemistry, and will have a strong record of excellence in teaching. Experience of small-group teaching would be a distinct advantage, as would
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. Candidates must have a PhD in a relevant field and sufficient breadth and/or depth of specialist knowledge in their chosen discipline to be able to teach to a high standard. They should also have evidence of
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grant funding remaining in place. Holding a PhD in Music or a related discipline and with a record of, or clear potential for, outstanding research, you will be a scholar whose research activities fall