41 computer-science-graduate-internship PhD positions at Chalmers University of Technology
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Biomedical Engineering conducts leading research in image analysis, computer vision, and machine learning, with a growing emphasis on generative AI and AI for scientific discovery. Our mission is to develop
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cross-layer defenses that ensure secure and efficient AI model development at scale. Information about the division The department of Computer Science and Engineering is strongly international, with
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of Computer Science and Engineering (CSE)Chalmers University of Technology University of Gothenburg You will be part of the Computing Science Division The appointed candidates will also join a vibrant community of over
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Sweden at the forefront of computational life sciences and AI research. The PhD student will belong to the graduate school within the Wallenberg AI, Autonomous Systems and Software Program (WASP). WASP is
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vulnerabilities and proposing effective defenses, the project seeks to make the next generation of the Internet more secure, resilient, and trustworthy. About us The Department of Computer Science and Engineering
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The Department of Architecture and Civil Engineering (ACE) at Chalmers University of Technology has approximately 250 employees, encompassing a broad theoretical and practical knowledge base. In ACE, the Division
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the Department of Bioproducts and Biosystems at Aalto University, Finland, specializing in biobased materials and chemical engineering. The successful candidate will be admitted to the Graduate School in
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AIPhD in computational modelling RAM³ is a WASP-WISE NEST project This recruitment is connected to the Wallenberg Initiative Materials Science for Sustainability All early-stage researchers recruited
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, and fellow PhD students Take advanced-level courses within the Graduate School of Shipping and Marine Technology , specializing in Maritime Environmental Science Contribute to departmental teaching
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machine learning, computer vision, and materials science. The focus of this position is on development of neuro-symbolic models for the effective behaviour of the complex microstructure of recycled