265 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "University of Waterloo" research jobs at University of Oslo
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PhD Research Fellow in Theoretical and Computational Active Matter Physics for Glioblastoma Invasion
English requirements for applicants from outside of EU/ EEA countries and exemptions from the requirements: https://www.mn.uio.no/english/research/phd/regulations/regulations.html#toc8 Grade requirements
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: https://www.mn.uio.no/math/english/research/groups/several-complex-variables/index.html https://www.mn.uio.no/math/english/research/groups/operator-algebras/index.html The Faculty of Mathematics and
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credentials. Required qualifications: Master’s degree or equivalent in mathematics, physics, control, cybernetics, computer engineering, automation, or related fields. Foreign completed degree (M.Sc.-level
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recently funded centre of excellence (Integreat). Integreat collects scientists from statistics and computer science and offers a flourishing machine learning community, including many PhDs and PostDocs
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of the post. Candidates without a master’s degree have until 1st of July 2026 to complete the final exam. Strong programming and artificial intelligence/machine learning skills. The candidate’s research
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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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July 2026. The research group studies functional immunogenetics and adaptive immunity - particularly in relation to autoimmune diseases (https://www.med.uio.no/klinmed/english/people/aca/lmsollid
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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
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laboratory analytical methods (e.g., chromatography, mass spectrometry). Familiarity with AI or machine learning applications relevant to environmental data analysis. Basic knowledge of GIS/mapping tools