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Description Are you excited about using large-scale AI to accelerate scientific discovery? Join a Horizon Europe project developing next-generation scientific foundation models that combine knowledge graphs
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, PlasmaObs, LCRS, Moonlight and Henon. You are encouraged to visit the ESA website: https://www.esa.int/ Field(s) of activity/research for the traineeship Many challenges and trends will affect the operations
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, by the measurement of Earth’s oblateness in 1958. Measuring the gravity field reveals Earth’s state of mass distribution and its dynamics. It also provides the geoid as a reference for sea level
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, and participate in outreach activities that will be generally, but not exclusively, related to your research topics. You are encouraged to visit the ESA website: https://www.esa.int/ Field(s) of
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, allowing demand flexibility services, distributed Energy Resources (DER), efficient operation, relevant savings in network investments, and the participation of consumers. Europe requires large investments
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of the parameter space in relation to the statistical model. One of the main goals of SLT is to quantify the complexity of such models w.r.t. the data generating process (and some prior probability distribution
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will develop novel and privacy-preserving algorithms that allow distributed devices (smartphones, wearables) to learn from new data streams over time (Continual Learning) while collaborating globally
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out spatially distributed measurements with for example shallow-depth geo-radar. You will be based at the department of Geoscience & Engineering (GSE) within the faculty of Civil Engineering and
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the next generation of protein-based nutrient delivery systems for food applications. What you are going to do You will investigate how multivalent mineral ions interact with casein phosphopeptides and how
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main contribitoin will be in the co-developing of a toolset (aim of WP2 of the project) to simulate a circular society and the transition to it, in particular focussing on the spatial distributions