28 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"NOVA.id" Postdoctoral positions in Sweden
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relevant field (e.g. computer science, artificial intelligence, machine learning, computer vision, animal science, biology, veterinary medicine, or a related discipline) have documented experience in
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-disciplinary research at the intersection of artificial intelligence, robotics, machine learning, and human-robot interaction. Subject area The subject area for this position is Computer Science. Background
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strong computational–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
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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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. 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 time and space, how this affects
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factor that strongly modifies turbulence, pressure drop, and heat transfer. Unlike conventional machined roughness, AM roughness is characterized by randomness, porosity, and powder adhesion, producing
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for machine learning, e.g. PyTorch or TensorFlow. Strong ability in spoken and written Swedish. Assessment of the applicants will primarily be based on scientific merits and potential as researchers. Special
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be implemented in collaboration with other groups at Department of Molecular Biology, providing excellent opportunities for the prospective candidates to expand the professional network and acquire
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of the following areas: state models, time series analysis, computational statistics, unsupervised machine learning, optimisation, model predictive control. Experience in financial mathematics. Having high integrity
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their doctoral degree earlier may also be eligible. Special reasons include absence due to illness, parental leave, appointments of trust in trade union organizations, military service, or similar circumstances