85 computer-programmer-"https:" "https:" "UNIS" "https:" "https:" "https:" "https:" "UNIV" "UNIV" scholarships at Nature Careers
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BUG-ID is a Marie Sklodowska-Curie Doctoral Network project, funded by the European Commission, Horizon Europe Program. Commencing its activities in January 2026, the Network will provide PhD
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in the Medical Life Sciences program Complete your PhD at Kiel University (CAU), with a doctoral degree awarded either through the Faculty of Engineering or the Faculty of Mathematics and Natural
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from at least two prominent international universities, with secondments in industrial partners The project offers a high-level doctoral training programme, providing a unique toolbox of cutting-edge
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at the University of Vienna. In particular, we offer a position for a university assistant (pre doc) in the Group of Univ.-Prof. Dr. Thomas Hummel at the Department of Neuroscience and Developmental Biology. Our
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Smet ( https://desmetlab.sites.vib.be ) and F. Van Breusegem ( https://vanbreusegemlab.sites.vib.be ) have expertise in abiotic stress signaling and in advanced molecular profiling, including mass
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established Systems Neuroimmunology Laboratory at LMU Munich (www.m-kaufmann.com ) is seeking a motivated and creative PhD candidate passionate about combining immunologic methods and advanced computational
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and professional life; offers of mobile and flexible work PhD Buddy Program family-friendly company policy with childcare facilities, e.g. nursery close to the company free assistance program for
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transporters are LAT1, SNAT2 and PAT1 as these have all been implicated in cancer. The project will do this via computational modeling and design using AlphaFold3.0 and available protein structures and ligand
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with a track record of intense mutual collaboration Structured PhD-training programme with a wide range of and professional development opportunities A respectful and appreciative work environment within
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About us VIB.AI, the VIB Center for AI & Computational Biology, is a research center dedicated to integrating machine learning with deep biological insight to understand complex biological systems