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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
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systems increasingly provide personalized recommendations in domains such as nutrition and lifestyle. However, many recommender and prediction systems rely heavily on opaque machine learning techniques
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! Recent advances in EO, such as dense satellite time series, rapid data access, and machine learning, have enabled the detection of deforestation, fires, floods, agricultural activities, and land cover
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restrictions may apply based on Dutch and EU immigration laws. Such candidates may be eligible for an “orientation year ” in the Netherlands or a visa as a “knowledge migrant ”. Where to apply Website https
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animal breeding and genomics activities (research and education) of Wageningen University & Research (Research of Animal Breeding and Genomics | WUR ). Where to apply Website https
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Breeding and Genomics Group | WUR . Where to apply Website https://www.academictransfer.com/en/jobs/358906/phd-position-welfare-assessment… Requirements Specific Requirements You are a highly motivated
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“learning from nature” approach to explore how novel protein crops and their close relatives interact with neighbouring plants and the wider ecosystem, translating these insights into biodiversity-positive
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understanding needed to guide crop improvement, support breeding strategies, and design resilient ideotypes for future Dutch protein landscapes. Where to apply Website https://www.academictransfer.com/en/jobs
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perspective. The second PhD position within this work package will focus on ‘learning from nature’. Together, these complementary perspectives will contribute to an integrated, system-level approach