286 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions in Sweden
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schools History News 2026 School Introduction Registration Program Recordings Questions Committees Sponsors Contacts Repository Lectures by topic Lectures by author Search lectures 2025 2024 2023 2022 2021
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the application of machine learning to optics, touching upon aspects of computational electromagnetism and inverse design. Information about the project and division Structured optical materials, such as
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to applied projects linked to societal needs. Key areas include computational mathematics, optimisation, biomathematics, statistics, and data science, supported by an active PhD programme. Our
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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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, robotics, machine learning, and human-robot interaction. Subject area The subject area for this position is Computer Science. Background The focus of the project is artificial intelligence (AI) and its
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scientific curiosity Mastery of data visualization and scientific communication Extensive knowledge of relevant machine learning and AI techniques Self-motivated individual with ability to work independently
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measurements from real projects, statistically analyse them, and conduct experiments with modern machine learning techniques and generative AI. A strong background in software engineering as well as some
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Extensive knowledge of relevant machine learning and AI techniques Self-motivated individual with ability to work independently Teaching and mentorship abilities or interests in personal development A
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position is hosted by the Division of Computing Science and specifically within the Programming Languages group that currently consists of 11 senior researchers and 9 PhD students that are working
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. Documented knowledge and experience in computational metabolomics, computational biostatistics, statistical and machine learning, involving analysis of biological multi-modal and multivariate data, or related