261 machine-learning "https:" "https:" "https:" "https:" "U.S" Postdoctoral research jobs in Sweden
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Home EMA The European Magnetism Association Executive Board General Council Documents Membership EMA news Communication Social Networks Mailing Event Dissemination Rules All news EMA editorials Obituaries Awards beyond EMA Materials 2023 survey Commitments Young EMA EMA Awards Technical...
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–experimental feedback loop central to the project. Subject description Recent breakthroughs in deep learning–powered protein design, recognized by the 2024 Nobel Prize in Chemistry, have enabled the creation
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imagine recruiting either a postdoc with thorough training in biochemistry structural biology who is eager to learn virology, or a postdoc with a strong background in molecular, mechanistic virology who is
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who completed their doctoral degree before that may also be eligible. Special reasons include absence due to illness, parental leave, appointments of trust in trade union organizations, military service
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Laue-Langevin (ILL), France, the International Institute of Molecular Mechanisms and Machines, (IMOL), Poland, and the Leicester Institute of Structural and Chemical Biology, United Kingdom. Your work
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located at SciLifeLab in Stockholm. Our research is focused on cell biology, spatial proteiomics and machine learning for bioimage analysis. The aim is to understand how human proteins are distributed in
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the official date of completion. Exceptions to the three-year eligibility limit may be made for documented circumstances such as parental leave, sick leave, or military service. The following experience will
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Machines, (IMOL), Poland, and the Leicester Institute of Structural and Chemical Biology, United Kingdom. Your work may include clinical and biomedical projects. It may also include technique development
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Machines, (IMOL), Poland, and the Leicester Institute of Structural and Chemical Biology, United Kingdom. Your work may include clinical and biomedical projects. It may also include technique development
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. The primary objective is to develop computational methods, using deep learning–based protein design, for the successful design of 2D lattices. These methods will then be applied to generate designs targeted