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Field
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Imaging Across Species The position is suitable for part-time work. About the Project The project aims to unravel complex interactions between the brain and the cardiovascular system using advanced MRI
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to the Autism and Neurodevelopment Clinic both from within the M Health network and UMMCH as well as from the community. We see patients across the spectrum and specialize in complex cases where patients have
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of Complex Networks, is funded by WASP, the Wallenberg AI, Autonomous Systems, and Software Program. Here, we use systems and graph theoretical tools to describe dynamic behaviors of large-scale interconnected
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northern Sweden create enormous opportunities and complex challenges. For Umeå University, conducting research about – and in the middle of – a society in transition is key. We also take pride in delivering
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, and engage with a vibrant network of national and international collaborators. The recruited candidate will work in the AIMLeNS lab lead by Assoc. Prof. Dr. Simon Olsson at Chalmers University
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. The appointee will work on a project focused on next-generation communication and sensing technologies for enhancing safety and performance in intelligent networked systems. The appointee is expected to make
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for therapeutic intervention. Initially focused on tools to study human protein complexes, the lab has expanded to novel screening platforms in human cells for applications such as Deep Mutational Scanning and
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(Faculty of Civil Engineering and Geosciences) and work closely with Dr Louise Nuijens and an (inter)national network of collaborators. QUASI offers a unique opportunity to combine cutting edge observations
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facilities in partnership with the computational science community. We help researchers solve some of the world’s largest and most complex problems with our unique combination of supercomputing resources and
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networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large language models Statistical learning theory and complexity analysis