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application! We are now looking for a PhD student in Computer Vision and Learning Systems at the Department of Electrical Engineering (ISY). Your work assignments Your task will be to analyse and adapt vision
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The PhD student will join a world-leading research environment at the Chalmers Security and Privacy Lab . Software is often the root cause of vulnerabilities in modern computing systems. We develop
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of algorithms, data structures, high-performance computing, machine learning and microbiology. The position at the Department of Molecular Biology at Umeå University is temporary for four years to start
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submissions in clusters Further details The position is funded (Salary) via the SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS; https://www.scilifelab.se/data-driven/ ), a 12-year
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: https://liu.se/en/article/open-positions-at-isy . The employment When taking up the post, you will be admitted to the program for doctoral studies. More information about the doctoral studies at each
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funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you interested in accelerating Sweden’s transition to green hydrogen by combining 3D
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Department of Forest Ecology and Management Third-cycle subject area Forest Management Description of the doctoral project This PhD position focuses on social dimensions of ecosystem restoration. It
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Collaboration Conduct research together with academic, industrial, and healthcare partners in a highly collaborative environment. Who we are looking for A highly motivated PhD candidate excited by computational
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-skogsgenetik/ Read more about our benefits and what it is like to work at SLU: https://www.slu.se/om-slu/jobba-pa-slu/ PhD Student: DDLS integrative pangenomics of polyploids Project description This PhD project
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you interested in working on robust methods for statistical learning