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elucidation of membrane protein complexes and integrates fundamental cell biology and structural biology by cryo- electron microscopy. The lab has a strong track record in investigating scramblases and their
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model-based control tailored to systems like NudgeFlow. The framework decomposes the global control problem into smaller local problems for each zone or room, enabling independent optimization with local
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1-D and 2-D modelling approaches fail to capture the complex three-dimensional effects critical to high-frequency, high-efficiency operation in modern converters. The PhD candidate will: 1
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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locally stored internal models of the environment. With existing edge solutions as baseline, a design solution will be explored to cope with the hardware constraints and the impact on energy
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-pathogen interactions using in vitro model systems mimicking chronic diseases. The project foresees ample collaborative opportunities with research groups in the MICRO-PATH consortium, spanning
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highly complex task, as sparse instrumentation does not guarantee direct sensing at all fatigue-critical locations of the substructure’s primary steel. Analytical solutions – so-called virtual sensing
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Saelens team. Research Project In this research project you will develop probabilistic deep-learning models that automatically extract biological and statistical knowledge from in vivo perturbational omics
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electrophysiology to translational models, including animal studies and analyses of human tissue samples. This full-stack methodology enables us to directly link molecular channel function with disease phenotypes
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improve the efficiency, maneuverability, and noise performance of drones and other multirotor aircraft, but their deployment requires more advanced modeling and control methods. The PhD will focus