22 machine-learning "https:" "https:" "https:" "https:" "https:" "U.S" Fellowship positions at University of Bergen in Norway
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centres at Faculty of Science and Technology. Read more about the faculty and departments. ess, click here . Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/296272/phd-research
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as a PhD candidate at UiB. Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/295159/phd-research-fellow-in-ph… Requirements Research FieldPhysicsEducation LevelMaster Degree
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Claireaux tells about life and work as a PhD candidate at UiB. Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/293286/phd-research-fellow-in-ma… Requirements Research FieldGeosciences
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, and relevance for the AI centre and Work Package 2. The department will host an online orientation meeting for the position 8 January 2026 at 14.00 hrs (CET). Participate at: https://uib.zoom.us/j
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at 14.00 hrs (CET). Participate at: https://uib.zoom.us/j/62281498137?pwd=Qakqii2iD8DxRLgrArHcugDrNKyEbW.1 Project proposal: The artistic research project proposal should place the project in a subject
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modelling tools. This PhD position aims to achieve to develop by the use of automatic picking, rather than manual, travel time picks, and the application of machine learning methods to reliably pick relevant
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position (100%, three years) is related to finance and insurance. The theme of the research project will lie within areas such as: simulation and risk modelling using advanced statistical and machine
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datasets from laboratory experiments will be provided to support simulation and verification of the resulting model. Replicate and learn a theoretical model for wave and current interaction by posing
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exam before 15.06.2026. It is a condition of employment that the master's degree has been awarded. Background in optimization is required. Experience in machine learning is an advantage. Familiarity with
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solvers, with the goal of exploiting models of various complexity, ranging from high-performance computing, via reduced-order models to data-driven (machine-learned) representations. In particular, we