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PhD Position in Theoretical Machine Learning – Understanding Transformers through Information Theory
, you’ll also join WASP —Sweden’s largest individual research program ever, offering unparalleled resources, networking and career opportunities. Be part of shaping the future of AI! Project overview
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program, the speech and language pathology program and the biomedical program. For more information about the Department of Biomedical and Clinical Sciences, please follow: https://liu.se/en/organisation
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Are you passionate about applying computational approaches to solve problems in biomedicine? We are now looking for an Industrial PhD student in Data-Driven Life Sciences to work on a cutting-edge
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interdisciplinary backgrounds and expertise to foster cutting-edge research with high clinical relevance. Project Description Imaging methods such as magnetic resonance imaging (MRI), computed tomography (CT), and
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part of the national research program WASP. Wallenberg AI, Autonomous Systems and Software Program (WASP) is Sweden’s largest individual research program ever, a major national initiative for
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Are you passionate about applying computational approaches to solve problems within chemistry and biology? We are now looking for an Industrial PhD student in Data-Driven Life Sciences to work on a
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) program. Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular
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build the sustainable companies and societies of the future. The EISLAB division of the Department of Computer Science, Electrical and Space Engineering conducts research within Cyber-Physical Systems
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, computational modelling, bioinformatic analysis, and experimental vascular biology. Based in a dynamic translational research environment of data-driven life science, computational imaging, and vascular surgery
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Sintorn, Professor in digital image processing, at the Department of Information Technology and conducted alongside researchers developing computational methods with a particular focus on deep learning and