12 machine-learning-"https:"-"https:"-"https:"-"U.S" Fellowship positions at University of Bergen
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30th April 2026 Languages English English Norsk Nynorsk English PhD Research Fellow in Mathematics focused on the application of geometry to machine learning Apply for this job See advertisement UiB
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the Department). The position is financed by the University of Bergen. About the project/work tasks The PhD project aims to investigate how methods from Scientific Machine Learning (SciML) can enhance modelling
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the use of modern machine‑learning methods within applied mathematics—particularly physics‑informed learning, anomaly detection, data‑driven modelling, and the construction of surrogate models grounded in
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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
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Centre SVT is an interfaculty centre with 10 permanent academic staff, 2 postdoctoral fellows, and 7 PhD candidates. Staff and PhD candidates conduct research, teach, and engage in outreach in the field
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equivalent education in climate dynamics, meteorology, oceanography, applied mathematics, physics, computer/data science or related fields or must have submitted his/her master's thesis for assessment prior
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-promoting work (e.g. teaching at the Department). The position is subject to financing by the project GRAIL (“Gamma Radiation from the Atmosphere for Investigation and Learning”), Maria Skłodowska Curie