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materials and technologies. Using advanced computational modeling and machine learning, we seek to elucidate the mechanisms governing the self-assembly of lignin in different solvents and the formation
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postdoctoral researcher and the supervisors Jens Sjölund (machine learning) and Leiting Zhang (battery sensing). The expected outcome is methodology and modelling tools for interpretable and generalizable
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application! We are now looking to appoint a postdoc in the field of AI and machine learning with a focus on scientific applications. Work assignments The primary focus of the postdoc positions is research in
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candidate will study and design nanophotonic structures and devices using machine-learning and optimization techniques. The postdoctoral position is a 2-year full-time employment position. We offer a
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design nanophotonic structures and devices using machine-learning and optimization techniques. The postdoctoral position is a 2-year full-time employment position. We offer a competitive salary, excellent
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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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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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of Medical and Translational Biology and the Wallenberg Centre for Molecular Medicine (WCMM) is offering a postdoctoral scholarship within the project “exploring sensory physiology in non-standard vertebrate
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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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/or spatial genomics, computational biology, machine learning, bioinformatics, and systems neuroscience. Prior experience with deep learning applied to biological data is a plus. Practical experience