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theory and methodology, and it maintains active collaborations with partners in other departments as well as in industry. Informal knowledge exchange within the department is highly encouraged and
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limitations. The field of interpretable machine learning aims to fill this gap by developing interpretable models and algorithms for learning from data. Meanwhile, the field of knowledge discovery and data
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at the intersection of the Web Information Systems Group (EEMCS Faculty, TU Delft, https://www.wis.ewi.tudelft.nl ) and the Knowledge and Intelligence Design Group (IDE Faculty, TU Delft, https://kind.fyi
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interpretable models and algorithms for learning from data. Meanwhile, the field of knowledge discovery and data mining has allowed us to obtain insights from large amounts of data for decades, and it is worth
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processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room at the faculty for ground-breaking research. We
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player. Domain knowledge of solar energy engineering, energy transtion, material science, modelling and data analytics is a strong plus. Experience with PV module fabrication or testing is a plus
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crucial knowledge gaps on the functioning of the coastal (ground)water system and develop much-needed, science-informed strategies to secure future access to clean freshwater for WASH and food production
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applicant. - The use of formal languages to specify and reason about distributed systems has been an object of intensive research. While verification support for these languages does exist, it is limited in
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difficult. This PhD research is envisioned to broadly follow one of three directions, but can be adapted to suit the interests of an excellent applicant. The use of formal languages to specify and reason
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leading knowledge institutions in its domain. The integral approach to challenges and the collaboration across various disciplines form the core of the unique Wageningen approach. Read the 5 reasons why