61 data-"https:" "https:" "https:" "https:" "Simons Foundation" Postdoctoral positions at Nature Careers in Denmark
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optimizing color selection for attentional purposes. The successful candidate will be required to design, program and conduct EEG-experiments, analyze and interpret EEG and behavioral data and present results
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quality and functioning, particularly in plumes near river outlets. This post doc project will rely on existing data as well as new field data of nutrients, carbon, and stable isotopes from riverine-coast
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Information For further details about the position, please contact Professor Vijay Tiwari at tiwari@health.sdu.dk Application deadline January 11, 2026, at 23:59 hrs. CEST Apply online: https://fa-eosd
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here . Further information Further information may be obtained from Carlos Acevedo-Rocha: cargac@biosustain.dtu.dk Google Scholar profile: https://scholar.google.com/citations?hl=en&user=yZDS88IAAAAJ
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career. Information on CGEN and its individual groups can be found at: https://cgen.ku.dk/ and on ICMM at: https://icmm.ku.dk/english/ . Project description The project will be decided in consultation
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analytical methods to large data sets The possibility for contract extension Flexibility in planning working hours Advanced professional training opportunities Possibility of participation in international
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refer to http://mbg.au.dk/ 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
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, creating CRISPR engineered cell lines, generating NGS data, including high-quality ChIP-seq data. The candidates with experience in both wet lab and bioinformatics will be able to do both (i.e. work in the
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refer to http://mbg.au.dk/ 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
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biology, epidimological data and AI-driven systems modeling. The successful candidate will develop and apply computational and machine learning approaches to decode the molecular and epigenetic mechanisms