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with incomplete information. Synthetic data offers a way out: realistic-but-artificial datasets that preserve the statistical, temporal and physical structure of real energy data without identifying real
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(PEM), and focused ion beam (FIB) imaging - can be combined with AI to reconstruct nanoscale chip structures and infer functional behaviour from physical layouts. The project addresses the challenge
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a Training and Supervision Plan, to structure the 4-year PhD trajectory. Perform the PhD research along four objectives: Analyse reward schemes for biodiversity – considering multiple actors (farms
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and Geosciences, with strong links with the Concrete Structures and Materials and Environment sections. Your supervisory team consists of Anne-Catherine Dieudonné, Wout Broere, Mladena Lukovic, and Erik
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design, fabricate, and characterize dynamic surfaces that form tactile features such as corrugations, Braille-like patterns, responsive fibres, suction-inspired structures, and switchable soft-hard
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improving robustness. The project will explore strategies related to 1) Object-attribute compositionality to replace exhaustive data requirements with structured concept learning, 2) Bias detection and
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in grasslands (NutNet) and along landscape gradients in forests (Veluwe), as well as in response to landscape-scale manipulation of forest structural heterogeneity along a nitrogen deposition gradient
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understanding of how light can be used to control polymer formation and structure. A key focus of the project will be chemical recycling. You will develop photocatalytic approaches to selectively break down
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coach you towards becoming an independent academic researcher. The proposal for this PhD project is attached. There, you find more details about its provisional aims and structure. This proposal should
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with incomplete information. Synthetic data offers a way out: realistic-but-artificial datasets that preserve the statistical, temporal and physical structure of real energy data without identifying real