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master’s degree with academic qualifications in digital health, data analysis, and/or machine learning applied to health research. Admission to the PhD program requires a 120 ECTS master’s degree, including
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master’s degree with academic qualifications in digital health, data analysis, and/or machine learning applied to health research. Admission to the PhD program requires a 120 ECTS master’s degree, including
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growth analysis and gas‑exchange measurements to assess photosynthesis, transpiration, and overall plant performance. Analyze plant samples for PFAS using high‑resolution LC/QTOF mass spectrometry. Carry
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knowledge for a better world. You will find more information about working at NTNU and the application process here. About the position A new PhD fellowship in path signatures, stochastic analysis, and
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techniques for studying dough and bread characteristics (e.g., rheology and texture analysis) Heat and mass transfer Mixing technology Statistical analysis Personal qualities: Inquisitive and driven
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unable to load from YouTube. Accept cookie and refresh page to watch video, or click here to open video) About the position A new PhD fellowship in path signatures, stochastic analysis, and learning from
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of the position. The successful candidate will have a solid theoretical foundation in one or more of the topics: Computational Mechanics, Finite Element Analysis (FEA), Numerical Optimization
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animal husbandry. The candidate can select where to place the main emphasis of the work and may also explore life-cycle analysis, human exposure, or cost-benefit modelling. You will work with NIBIO, NGI
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, Department of Physiology Analysis of biological and experimental data Preparing manuscripts that meet the requirements for publication in international journals and compile them into a doctoral thesis in
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experiences and skills will be emphasized: Experience in plant phenotyping, drought stress research, or root biology Familiarity with imaging technologies, statistical analysis, or quantitative data analysis