49 computer-science-intern "https:" "https:" "https:" Postdoctoral positions at Nature Careers
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. The Medical University of Vienna provides an excellent research environment including state-ofthe-art research core facilities and an international PhD program and various platforms which bring together
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and optimize advanced protocols (e.g., single-cell assays, CRISPR-based screens) Collaborate with an interdisciplinary network of computational biologists, clinicians, and international research
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, computer science, statistics, epidemiology, psychology, public health, psychiatry or a connected field Excellent research track record, including at least two first-authored peer-reviewed publications relevant
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(or near completion) in computer science, machine learning, statistics/biostatistics, computational biology, data science, physics, or a related field. Experience with modern deep learningframeworks (e.g
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Development Programme targeted at career development for postdocs at AU. You can read more about it here . At the Faculty of Natural Science at Aarhus University, we strive to support our scientific staff in
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sciences (e.g., medical sociology), Protestant/Catholic theology, medicine, law, psychology, political science, or nursing science Qualifications and experience in empirical research in the field of medical
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5-year undergraduate nanotechnology programme and nanoscience graduate programme (https://phd.nat.au.dk/programmes/nanoscience/) the center provides a full educational environment. In
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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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collaborate closely with internal and external partners to advance the project. Your profile The ideal candidate holds a PhD in biochemistry, structural biology or a related field, and has hands-on experience
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. Qualifications: PhD in Molecular Biology, Biomedicine, Human Physiology, Computational Systems Biology or similar fields. Proven expertise in LC/MS based metabolomics and/or bioinformatic analyses of complex omics