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Lund University Visiting Professors Programme Lund University invites expressions of interest for its Visiting Professor Programme. We seek individuals eager to engage with our vibrant research
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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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at the Artistic Campus. With approximately 75 students, around ten employees, and many guest lecturers, it is a dynamic and international environment. The Academy of Fine Arts offers a 3-year bachelor's program
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collaborations. The research group The position is in Ben Murrell’s group in MTC, based in the Biomedicum, in Karolinska’s Solna campus. The lab has worked across the experimental/computational interdisciplinary
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, second and third cycle levels. The department is responsible for ca. 30 courses within SLU's educational programs, e.g. the agronomy programs, the bachelor's program in biology and environmental science
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. These positions involve advanced numerical simulations and analysis of spacecraft data. The positions are full-time, 100% funded for four years and lead to a doctoral degree in Computational Physics. The expected
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) programme and research school Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures
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leading to production and harvesting in the regulated countries moving to unregulated countries. The position is part of a joint research program between Swedish University of Agricultural Sciences (SLU
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. The task is to understand phenomena like “model collapse” and implementing strategies to avert it, using tools from the Systems and Control field. Wallenberg AI, Autonomous Systems and Software Program (WASP
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and computational methods within quantum mechanics and statistical physics with the aim to design alloys for rare-earth-free high-performance permanent magnets. You will use computational techniques