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nematode community to N mineralization and N2O emissions in realistic soil conditions. In this project, we will set up unique multitrophic experiments controlling for the presence of specific trophic groups
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gap by (a) implementing a large randomized controlled trial, and (b) involving stakeholders (adolescents, teachers, parents, organizations) via focus group interviews. In a first phase, we will collect
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improves focus, while overload leads to inefficiency and cognitive fatigue. Novelty and Engagement: Generative AI will be used to introduce a controlled level of novelty in learning content and environmental
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Job description PhD position in computational neuroscience - Deep reinforcement learning closed-loop control for the treatment of epilepsy As part of the highly prestigious ERC Starting Grant
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Engineering, or equivalent. Candidates with background in operations research, systems engineering, control and optimization or in a closely related domain are strongly encouraged to apply. We offer a pleasant
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the impact of design measures improving aerodynamic robustness. In this research project, you will generate new capabilities for controlling the three-dimensional flow and further increasing the efficiency
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management of PXE focusses on symptom control and prevention as no treatment is available. This research project aims to evaluate the efficacy of genome-guided therapy in ectopic calcification, common in
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closed-loop control. The technology, developed through detailed computer simulations, will be validated with preclinical experiments. The candidate will be part of a multidisciplinary team working towards
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monitoring disturbances from both satellites and ground-based sensors. The latter is expected to contribute to the further development of the pylidar repository. This PhD project will be promoted by prof. Kim
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disciplines: computer science/engineering or biomedical engineering. You have an excellent academic record of accomplishment. In particular, you have a good command of, and a strong interest in, computer