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several related areas of expertise: generative AI for robotic planning and control, cognitive control, distributed perception and control, and HW-SW co-design of algorithms. Our research is applied across
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, in tropical rainforests of Latin America You will assist in the teaching activities at the department, specifically in the domain of systematic and evolutionary botany You will assist in the internal
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. Our research spans several related areas of expertise: generative AI for robotic planning and control, cognitive control, distributed perception and control, and HW-SW co-design of algorithms. Our
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functionality. Your work will involve designing advanced algorithms that efficiently utilize UWB signal features (RSSI, channel impulse response, phase and amplitude data, Doppler maps,..) to support both high
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machine. We develop quasi-Newton coupling algorithms for partitioned simulation of FSI, and we solve challenging FSI problems in the energy transition and in industry. This research is often in
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to constrain the physics involved in the formation of gravitational wave sources through the study of intermediate evolutionary stages that can be constrained through electromagnetic observations. The candidate
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machine. We develop quasi-Newton coupling algorithms for partitioned simulation of FSI, and we solve challenging FSI problems in the energy transition and in industry. This research is often in
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to ensure reusability and scalability. To achieve this, you will work with high-fidelity simulation tools, machine learning algorithms, and experimental condition-monitoring systems (accelerometers, acoustic
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algorithms need to be developed to determine the winners of the auction, as well as intermediate feedback that can be communicated to the bidders, to facilitate the bidding process. The market-based research
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theoretical background for MIMO related research, and have attended courses such as Information Theory, Signal and Systems, Modulation and Detection. Experience with OFDM or single carrier baseband algorithms