67 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "The University of Hong Kong" Postdoctoral research jobs at Nature Careers in Denmark
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planning, conducting, and publishing epidemiological studies using large-scale observational data, primarily register-based, focusing on women’s short- and long-term health outcomes within the specific work
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further information are invited to contact Associate Professor Niculina Musat (niculina.musat@bio.au.dk). Who we are The successful candidate will be employed by the Department of Biology at Aarhus
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proliferation and the faithful transmission of genetic information to daughter cells. However, replication forks are constantly challenged by a wide range of intrinsic and extrinsic stressors, including metabolic
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interpreting large-scale spatial transcriptomic data from multiple clinical trial. You will collaborate with an interdisciplinary teams of scientists and clinicians to develop bioinformatics pipelines and tools
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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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. The Section for Wildlife Ecology is situated in Aarhus and employs 35 staff members, including six affiliated with the bat research group. For more information on the Department see: http://ecos.au.dk/en/ What
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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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information For further information, please contact: Professor Torben Heick Jensen, thj@mbg.au.dk, phone +45 60202705 Application procedure Shortlisting is used. This means that after the deadline
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information For further information, please contact: Assistant Professor Emil Laust Kristoffersen, +45 29271306, emillk@inano.au.dk . Application procedure Shortlisting is used. This means that after
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at the Department of Electrical and Computer Engineering, Aarhus University, where we are advancing communication-efficient and distributed foundation model inference across the computing continuum