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Hochstenbach. This project is funded through a Vidi-grant from NWO, the Dutch Research Council. The DWELLWELL project will involve two PhD-candidates working with different methods on different research
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. The DWELLWELL project will involve two PhD-candidates working with different methods on different research questions. While housing is recognized as an important social determinant of health, this relationship is
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learning for interconnected systems (e.g., 6G and Edge AI platforms, self-driving vehicle vision) in collaboration with industry partners and domain experts. This PhD thesis is offered in the context
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-studies, mixing quantitative and qualitative methods to understand the impact of restoration on different values for society Where to apply Website https://www.academictransfer.com/en/jobs/360262/phd
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command of the English language (knowledge of Dutch is not required). Please note: Each project requires a different mix of skills and attitude. Please use the TU/e PhD Competence Profile to determine
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way so they will make a difference in our region and who is also enthusiastic about doing applied research. About the position Your activities may include: Initiating the development and implementation
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now As a successful candidate, you will be part of the international research project “Follow the money! REconstructing Belief systems behind Urban Intensification and Land-rent Distribution (REBUILD
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the money! REconstructing Belief systems behind Urban Intensification and Land-rent Distribution (REBUILD)”, funded by the Swiss National Science Foundation. Focusing on case studies in the Netherlands and
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of the following subjects: scalable data management, systems for machine learning, distributed and parallel systems, or cloud-based systems. We are especially interested in researchers who build working systems and
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is looking for an aspiring PhD candidate to research causal machine learning and uncertainty quantification for Earth Observation time-series. Currently, predictive AI in Earth Sciences relies heavily