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how geometry- and data-driven digital twins of wireless environments can support learning, inference, and coordination in physical AI systems such as robots, vehicles, or distributed sensing platforms
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at the Department of Electrical and Computer Engineering, Aarhus University, where we are advancing communication-efficient and distributed foundation model inference across the computing continuum
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and will have a permanent staff of 43 full, associate and assistant professors, a support staff of ~40 technical and administrative staff, ~150 PhD-students and ~100 postdocs and around 350 students
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at the Department of Electrical and Computer Engineering, Aarhus University, where we are advancing communication-efficient and distributed foundation model inference across the computing continuum
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intelligence within grid-connected power converters and variable-frequency motor drives with edge computing and machine learning capabilities. We offer a multidisciplinary, international, and friendly atmosphere
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information may be obtained from Professor and Head of Research Group, Frank Aarestrup on fmaa@food.dtu.dk or Associate Professor, Philip Thomas Conradsen Clausen plan@food.dtu.dk Read more about the DTU
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paths at DTU here . Further information Further information may be obtained from Professor Xenofon Fafoutis and Associate Professor Luca Pezzarossa . You can read more about ESE at www.compute.dtu.dk
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for physical AI systems that learn and adapt through continuous exposure to multimodal sensory and radio data, and acts upon real-world environment through distributed coordination and control. Emphasis will be
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computational scientists. The position offers a unique opportunity to work at the interface of landscape ecology, biodiversity science, climate mitigation, and sustainable agriculture, contributing directly to
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computational scientists. The position offers a unique opportunity to work at the interface of landscape ecology, biodiversity science, climate mitigation, and sustainable agriculture, contributing directly to