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Umeå University is one of Sweden’s largest higher education institutions with over 41,500 students and about 4,600 employees. The University offers a diversity of high-quality education and world-leading research in several fields. Notably, the groundbreaking discovery of the CRISPR-Cas9...
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distributed WaRM experiment (for details see here: https://onlinelibrary.wiley.com/doi/10.1002/ece3.9396). The employment is fulltime for three years. The deadline for applications is March 26, 2026 and the
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delivery. The postdoc will join Professor Nathaniel R. Street’s team at UPSC, working closely with Laszlo Bakó (molecular biology) and Torgeir R. Hvidsten (comparative genomics). The environment provides
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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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Research School will be expanded with the recruitment of 25 academic and 7 industrial PhD students. During the course of the DDLS program more than 260 PhD students and 200 postdocs will be part of
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within the university. Tasks may change over time as communication and engagement avenues evolve, so you are required to stay current on popular technologies, trends, and algorithm patterns. Other
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objective of the project is to develop knowledge, models, and algorithms for physics‑informed autonomous control of heavy machinery in uneven and deformable terrain. Specific project tasks include fundamental
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. The last application date is March 30, 2026. Project description The postdoc position is supported by the Water4All Transnational Project: Impacts of climate, N and P deposition and land use on water as a
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biogeochemistry discipline, including Physical Geography, Biology, Environmental Sciences, or similar, and with previous postdoc experience. The ideal candidate should have strong expertise in aquatic
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, experience working with the PyTorch framework, documented ability to develop algorithms and implement them in efficient code, and experience in statistical modeling, optimization or numerical methods, as