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(Computational) Social Sciences, Data Science, or a related discipline (e.g., sociology or human geography) by the start of the position; has proven experience in working with large datasets and quantitative
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agriculture to function well within the landscape. In this PhD, existing monitoring network data and locally collected field data will be available for the modelling work, in addition to freely available
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large number of distinct but interacting components. To address these challenges, this project aims to contribute to the development of a control theory that is inherently modular, i.e., that allows
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to the TopTreat consortium by analysing and optimising new personalized strategies for osteoarthritis diagnosis and care, based on collected clinical data and technological innovations (TopTreat-onderzoek artrose
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materials. For the second challenge, achieving cooperative effects by the controlled organisation of a large collection of molecular motors, one approach involves embedding molecular rotary motors in
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explore how brand narratives evoke emotions, build relationships, and influence consumer decision-making. By leveraging insights from behavioral science (psychology), data analytics, and AI-driven
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large part by members of the precariat rather than the traditional proletariat, has once again put labor organizing on both the political (and academic agenda). From a theoretical perspective, this
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the breeding of complex resilience traits for several crops in different growing systems. This collaborative effort involves four universities and numerous companies. It encompasses scientific research, data
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and have access to state-of-the-art industry experts, data and knowledge, allowing you to make an impact during your PhD research. In this position you will work with real world data and models, aimed
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for the new green steels compositions, including impurities and tramp elements. These models should enable density-functional-theory (DFT) accurate large scale atomistic simulations of defects including