52 machine-learning "https:" "https:" "https:" "https:" "RAEGE Az" Fellowship positions at University of Oslo
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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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-working candidate. Main responsibilities Develop and apply machine learning and statistical modeling techniques, including novel AI architectures, for the analysis of complex traits and precision prediction
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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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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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pressure-build ups in potential multi-site storage licenses. The research will help to suggest best practices for machine learning integration in de-risking CO2 storage sites. We seek a candidate with a
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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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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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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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: 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