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position for candidates interested in interpretable AI, stochastic optimal control, deep learning and high-impact research in sustainable mobility. About us The position is located at the Systems and Control
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. The project focuses on power-aware computing, thermal optimization, and sustainable electronic design, targeting critical applications in aerospace, healthcare, and industrial automation. Hosted by the renowned
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garments into recycle, reuse, and manual-review streams; this PhD project tackles the core challenge of designing and optimizing a high-throughput hyperspectral imaging system, fused with complementary
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and machine learning to tackle the complexity of force allocation and motion planning under uncertainty and actuator failures. The project combines theoretical research in stochastic optimal control
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The role will develop new AI methods for identifying the instantaneous state of a fluid flow from partial sensor information. The research will couple techniques from optimization and control theory
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academic partners in Europe and globally. Candidates with the following qualifications will be preferred: Educational background in power systems. Documented knowledge in optimization in power and energy
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sunlight, air and water. Electrodes are a central component of the novel bioelectrochemical platforms for energy harvesting and microbial electrosynthesis. Optimal design of the 3D geometry and material
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of Electrical Engineering . You will be supervised by senior researchers with expertise in robotics, machine learning, automatic control, and optimization. The group leads and participates in numerous
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functional priors from billions of years of evolution; how to compress measurements with controlled mixtures of molecules; and how to align models of laboratory experiments with observational human biology
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for Biomagnetism and Biosognalanalysis – ideally with you on board! The Project “Multi-channel transcranial current stimulation (mc-tCS): a novel approach to modulate smooth pursuit eye movement control in healthy