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The Department of Physics at Chalmers University of Technology invites applications for a postdoc position targeting machine learning in optics. In this position, you will become part of a
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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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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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transitions and universality for spectral statistics of random matrices and their applications in high-dimensional statistics, machine learning and probability theory. The Department of Mathematics at KTH
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for studying spatiotemporal protein interactions. The postdoctoral fellow will have the opportunity to: - Learn novel research techniques for genome-wide screens - Explore molecular mechanisms of mitochondrial
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groups working towards a common goal. For this postdoc project, we seek a dynamic and motivated candidate with an interest in computational electromagnetism, inverse design, and/or machine learning in
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and expertise in brain imaging (MRI), image processing and machine learning. Coordinating projects within the research group, supervising students and writing applications are also included in the role
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into mechanosensory corpuscles (Nikolaev et al., Sci Adv 2020; Nikolaev & Ziolkowski et al., Sci Adv 2023; Ziolkowski & Nikolaev et al., Sci Adv 2025). This is just the beginning and there is still much to be learned
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for molecular dynamics (MD), slashing computational costs by orders of magnitude and enabling breakthroughs in drug design and materials science. The position bridges machine learning and molecular science, with
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Railway Engineering is seeking a motivated and collaborative postdoctoral researcher for a project on developing machine learning tools for pavement management. The project is conducted in collaboration