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, or the application of machine learning to registry data is highly valued. Experience in statistical analysis, including the use of statistical software such as STATA, R, Python, or SAS, will be viewed positively
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. Strong (inter-)national network in field of application. Experience with high-performance computing (HPC) and large datasets. Experience with machine learning applied to geophysical signals. Experience in
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SFI FAST: PhD position in Microstructure/texture evolution during extrusion of scrap-based Aluminium
that you are particularly suitable for a PhD education. You must meet the requirements for admission to the faculty's doctoral program (https://www.ntnu.edu/nv/phd) PLEASE NOTE: For detailed information
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