296 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" Fellowship research jobs in Norway
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- University of Oslo
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programmes is a primary focus for the faculty's doctoral programme, PhD in educational sciences (UTVIT) (https://www.inn.no/english/research/doctoral-degree/educational-sciences/). It is a prerequisite that
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environment for the training and development of PhD candidates and postdoctoral fellows, including individually tailored career development plans with formal supervision and project-based learning. Secondments
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biology, advanced imaging, and machine learning. Colourbox via Unsplash Colourbox What skills are important in this role? The Faculty of Mathematics and Natural Sciences has a strategic ambition to be among
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criteria see https://www.nmbu.no/en/research/regulations-and-guidelines-doctoral-degrees-nmbu To be employed, you cannot have previously held a PhD position at NIBIO or with funding from The Research Council
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to apply: https://www.jobbnorge.no/en/available-jobs/job/291009/phd-research-fellow-in-criminology Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/291009/phd-research-fellow-in-cr
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integration of welfare technologies in the care systems for elderly people. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/292367/phd-research-fellow-in-human-robot
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about working and living in Norway can be found here: https://uit.no/staffmobility Application Please note that the application will only be assessed based on the information submitted by the application
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plays in society and how professional language functions, is learned, and used in different contexts. Participants in work package 2 will study how professional language is used in education, research
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Science About the project This PhD project integrates pharmacoepidemiology, causal inference, and machine learning to study real-world treatment patterns, effectiveness, and safety of monoclonal antibodies
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the areas of stochastic analysis and computational methods towards machine learning with focus on risk-sensitive decision making and control. Techniques may include forward, backward stochastic differential