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SFI FAST: PhD position in Microstructure/texture evolution during extrusion of scrap-based Aluminium
programming languages such as Python, FORTRAN, or similar, and an experience with using an FEA software. You must be fluent in spoken and written English. Your education must correspond to a five-year Norwegian
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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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system modelling. Very good programming and modeling skills, preferably Python or a similar programming language. Work and/or research experience in a field related to the topic of this PhD
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electricity/electronics, chemistry, and optics, as you will be working with advanced custom instrumentation. Experience with programming (for example Python/Matlab) and image analysis is highly recommended
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to conduct safe experiments. Experience with optical measurement techniques. Good programming and data analysis skills (e.g., Python, MATLAB, LabVIEW). You must meet the requirements for admission
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an advantage: Natural Language Processing; LLMs; R; Python. Experience with teaching and supervision will be considered an advantage. Very good skills in Norwegian or other Scandinavian language is an advantage
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processing, software-defined-radio and similar A solid background in programming and signal processing (C, Matlab, Python, …) Knowledge and experience with embedded systems are a strong plus (C, FPGA
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selection criteria Experience with behavioural-related experimental work Knowledge on programming in R/Python is beneficial Personal characteristics To complete a doctoral degree (PhD), it is important that
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analysis workflows (Python and/or Julia-based; HPC-oriented handling of large datasets). Depending on competence: contributing to research software development supporting simulations and/or data workflows
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interest in translational endocrinology and digital health technologies Basic programming or data science skills (R, Python) and interest in wearable data analysis are an asset Excellent command of written