40 affective-computing-"https:" "https:" "https:" "UCL" "UCL" positions at SciLifeLab
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, international, and outward-looking work environment located in the lively city of Gothenburg on the west-coast of Sweden. The position is funded by the fellowship scheme of the Wallenberg National Program for
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representatives at the University of Gothenburg can be found here: https://www.gu.se/om-universitetet/jobba-hos-oss/hjalp-for-sokande Application To apply for a position at the University of Gothenburg, you have to
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universities. SciLifeLab forms an internationally unique infrastructure and research community, bringing together groundbreaking life science technologies with data and AI expertise. Computational methods and
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at the spatial level in the colon (ERC Synergy) and the impact of spaceflight on the brain gene Swedish Research Council and Swedish National Space Agency). The postdoctoral research activities will focus
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will be part of a dedicated team with full end-to-end ownership of its products. You will work specifically with SciLifeLab’s digital infrastructure, delivering high-impact solutions to Sweden’s leading
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to the development of novel tools for cancer risk assessment with real potential impact on healthcare. Qualifications Requirements A doctoral degree or an equivalent foreign degree in computer science, statistics
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platforms and evaluation of new materials in interaction with biological systems to understand the underlying principles. For us, it is equally important to study the impact of materials on biological
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The Department of Gene Technology, at KTH Royal Institute of Technology, is looking to fill a position as Assistant Professor focused on innovative development and application of computational
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. Our research is focused on cell biology, spatial proteiomics and machine learning for bioimage analysis. The aim is to understand how human proteins are distributed in time and space, how this affects
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School of Electrical Engineering and Computer Science at KTH Project description Third-cycle subject: Computer science This project involves generative modeling to address missingness in mass