50 machine-learning-"https:" "https:" "https:" "RAEGE Az" Fellowship research jobs at University of Oslo
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) to Proteome Sciences, Frankfurt (Germany), University of Strathclyde, Glasgow (United Kingdom) and Capitainer AB (Sweden). For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job
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Machine Learning. We are looking for a motivated candidate, who has interest in both theoretical, methodological and applied research in anomaly detection in sequential data settings, and who is excited
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equations (PDE). Examples of models in the scope of the project include particle models, stochastic PDE and models from fluid dynamics and machine learning. What skills are important in this role
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optimization. Experience with quality-diversity methods is a plus. • Experience with machine learning and artificial intelligence. • Strong programming skills (e.g., Python, C++), and familiarity with ROS
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of Oslo for the project: DC14 - ESKAPE pathogen adhesion to cells and implant surfaces Supervisors Dirk Linke: https://www.mn.uio.no/ibv/english/people/aca/dirkl/index.html Håvard Haugen: https
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on other experiments within the Cosmoglobe network to broaden their scientific skills and network. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/289299/postdoctoral
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for the project: DC4 - The role of invasin-integrin interactions in Klebsiella and Enterobacter infections Supervisor Dirk Linke: https://www.mn.uio.no/ibv/english/people/aca/dirkl/index.html Co-supervisors: Håvard
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for a motivated PhD candidate to join our team at the University of Oslo for the project: DC14 - ESKAPE pathogen adhesion to cells and implant surfaces Supervisors Dirk Linke: https://www.mn.uio.no/ibv
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the final exam. Desired qualifications: Experience in areas such as machine learning, computer vision, control sys-tems, perception, control engineering, or autonomous systems Familiarity with ROS (Robot
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: https://www.mn.uio.no/ibv/english/people/aca/dirkl/index.html Co-supervisors: Håvard Haugen (Corticalis AS), Susanna Fagerholm (University of Helsinki) Project description The PhD candidate will study