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, (food) marketing, or related social sciences disciplines, strong analytical skills, experience with relevant statistical methods, proven interest in topics related to sustainable food systems, and strong
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an interdisciplinary research team; Excellent publication records; Experience in large-scale earth observation analytics; Experience in integrating multi-source remote sensing data with process-based or data-driven
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equations to simulate pollutant transport, mixing and biochemical processes. To enable rapid prediction, a machine-learning surrogate model based on Gaussian process regression will be developed and trained
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and secondments. • Blended Learning Approach: Our training combines intensive in-person workshops at partner institutions with regular interactive online seminars, journal clubs, and research
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studies, media studies, anthropology, and/or related disciplines; Familiarity with and keen interest in qualitative research methods; Independent thinking and critical analytical skills; Good collaboration
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with and keen interest in qualitative research methods; Independent thinking and critical analytical skills; Good collaboration skills and an ability to join interdisciplinary and intercultural academic
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enjoy working analytically with quantitative data, approaching research questions thoughtfully, and learning new methods and theories. You can work independently while contributing actively to a
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må du være oppmerksom på at enkelte funksjoner og tjenester ikke kan brukes, da de forutsetter at nettsiden kan huske de valgene du gjør. Du kan velge bort cookies fra Google Analytics her . Det er
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: · Learning how to express software requirements precisely using formal models. · Using these specifications to automatically generate test cases for software systems and code. · Exploring how test
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to the adaptation of the Environmental Noise Directive for these new technologies. Your main focus will be to develop machine learning-based drone noise models that will be able to generate an accoustic footprint