314 assistant-professor-computer-science-data Postdoctoral research jobs at Nature Careers
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of chemistry, biochemistry or comparable Salary group 13 TVöD Temporary contract until 30.06.2026 under the reserve that funds are granted Full-time / suitable as part-time employment The Bundesanstalt für
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Research Associate in Medicinal Chemistry to work on an NHMRC funded project with Professor Peter Rutledge, Professor Richard Payne , and Dr Jessica Zhong , in collaboration with Professor Warwick Britton
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at Baylor University is seeking multiple postdoctoral research associates with expertise in either organic chemistry or chemical biology. Please see below for specific information about desired candidate
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PhD Student / Postdoctoral Researcher (gn*) Molecular Biology Reference Number: 10836 Fixed term of 3 years | Full- or Part-Time (65% or 100%) | Salary Grade TV-L E13 | Centre of Reproductive
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computational biology/chemistry, machine-learning for biological or chemical data, and drug discovery/design. Mentorship is taken seriously and every effort will be made to ensure the candidate is able to achieve
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collaboration between research groups at several departments at Aarhus University. For further information, please contact Professor Kurt Gothelf +45 60 20 27 25 kvg@chem.au.dk Application procedure Shortlisting
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/ for further information about The Department of Molecular Biology and Genetics and to https://nat.au.dk/ and http://www.au.dk/ for information on Faculty of Natural Sciences and Aarhus University
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, probabilistic models Representation learning, self-supervised learning, foundation models Data analysis, non-linear statistics, knowledge management Your profile PhD in Computer Science, Bioinformatics
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of these patients. The goal of this project is to combine cutting-edge multi-omics technology, data analytics, machine learning and clinical samples from the human eye to decipher new insights into disease mechanisms
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currently exploring a range of exciting topics at the intersection between computational neuroscience and probabilistic machine learning, in particular, to derive mechanistic insights from neural data. We