283 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" positions at University of Oslo
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of AI and in particular machine learning (ML). As today’s mainstream AI/ML workloads often resort to large-scale and energy-hungry supercomputers, it is necessary have a more critical look at how HPC
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Africa and Europe. The network will consist of 15 PhDs, that together will work and learn as an international cohort and collaborate across projects to bring together insights anchored in different sectors
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. The successful applicant must be able to teach at all levels and to supervise Master and PhD students. The successful applicant may furthermore be required to take on other teaching duties and administrative tasks
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(NELO), revealing the branchial cavity as an important region of the fish immune system. (https://www.science.org/doi/10.1126/sciadv.adj0101 ) (https://www.frontiersin.org/journals/immunology/articles
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educational system. Strong background in molecular modeling, molecular dynamics simulations, or computer-aided drug design. Proven record of programming language through publicly available Github/Gitlab
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dynamics simulations, or computer-aided drug design. Proven record of programming language through publicly available Github/Gitlab or similar repositories. Experience in the cell biology lab Fluent oral and
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Computers and Electronics - NTNU. https://www.ntnu.edu/nice Jarli & Jordan/ UiO via Unsplash Jarli & Jordan/ UiO What skills are important in this role? The Faculty of Mathematics and Natural Sciences has a
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protection. For more information about the Digital Security Research Group, see https://www.mn.uio.no/ifi/english/research/groups/sec/ Jarli & Jordan/ UiO via Unsplash Jarli & Jordan/ UiO What skills
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stimulating research environment. The project will be supervised by Prof. Rafal Ciosk and co-supervised by Prof. Marianne Fyhn: https://www.mn.uio.no/ibv/personer/vit/rafalc/ https://www.mn.uio.no/ibv/english
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kind of machine learning algorithm, provides more accurate data than traditional data collection methods, e.g. paper-based surveys. This data is valuable to several stakeholders: i) architects and urban