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Bilevel programming (BP) is a powerful mathematical framework for modeling hierarchical decision-making processes involving two players: a leader and a follower. In energy network design, for example
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processing, and user-friendly GUI-based analyses for clinical and physiological research. You will combine Python-based software development, biomedical signal processing, and FAIR data design, and contribute
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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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that strengthens collaboration, reduces time-to-job, and drives innovation for a climate-neutral society. In this position, you will design and optimize learning communities that integrate learning
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. Based on these insights, you will formulate design rules to predict optimal loading conditions and release mechanisms, supporting experimental optimization. We expect you to be able to work with a high
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skills for functional genomic screen design and analysis. You will build CRISPR tools, design optimized pooled genetic screens (e.g. Perturb-seq–based approaches), and troubleshoot the experimental
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of the urban soil/subsoil in Amsterdam required for optimal tree growth. Ecosystem services include: storing water in the unsaturated zone; draining water via groundwater; sequestering carbon; filtering and
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into model-predictive control (MPC) or reinforcement learning (RL) frameworks to compute optimal exoskeleton assistance in real time. Validating the developed methods in human experiments using motion capture
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. The goal of these two postdoc positions is to contribute to the modelling, simulation, and optimization across different LDES technologies, from device (ESS+inverter) to system level (grid integration) under
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imaging inside human long bones (https://doi.org/10.1007/978-3-030-91979-5_10). For optimal imaging inside bone, one must consider the challenging 3D wave physics imposed by bone tissue: wave refraction