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capabilities, existing technology can only handle relatively small-scale problems. Information In the SymBi project (Exploiting Symmetries for Faster Bilevel Optimization Algorithms), we address this limitation
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to a platform that supports researchers in understanding and analyzing complex respiratory time-series data. You will merge codebases, implement dedicated data containers, port and optimize signal
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on the results of the Erasmus+ project EDDIE. When it comes to the research part: This PostDoc project explores how artificial intelligence (AI) can be leveraged to optimize energy portfolios for local energy
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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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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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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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. 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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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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hardware (battery limitations, intermittent connectivity, limited compute/storage). Experience implementing or optimizing models for on-device or edge execution is a strong plus. Project Organizational