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-enabled adaptation. The aim is to develop theoretically grounded yet practically deployable algorithms that allow multi-agent robotics to operate robustly in dynamic, uncertain, and interactive environments
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analyse and develop new, well-founded methods and learning algorithms that extend the boundaries of existing techniques - for example, with respect to expressivity, generalization, interpretability
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mathematical theory and algorithm development as well as engineering methods that enable robust and efficient practical solutions. As society and technology evolve toward increasingly large‑scale, data‑intensive
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energy recovery linac (ERL) demonstrator at IJCLab, Orsay. ERLs offer a promising way toward the development of future colliders, particularly by providing excellent beam quality while drastically reducing
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Genomics at Harvard Medical School Several positions are available in the Park Lab (https://compbio.hms.harvard.edu/ ). The aim of the laboratory is to develop and apply innovative computational methods
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the activities of GT3. The initial phases will focus on studying the ideal frameworks for creating the IT platform and developing AI algorithms for data analysis. In particular, the data storage structure will be
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environment who will supervise the PhD and collaborating with the rest of the Doctoral Network fellows. Where to apply Website https://cv.newton-6g.eu/ Requirements Research FieldEngineering » Electrical
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will focus on developing theoretical and algorithmic foundations for goal-oriented, semantics-aware communication enabling timely and reliable cloud-to-agent interactions. For more details on semantic
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and limited resources (fleet size, mobile and fixed charging infrastructure). This project aims to address these challenges by developing novel mathematical models and algorithms to support real-time
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3D environments. • Design of a robust control architecture to ensure autonomous navigation using information from the optical localization system (development of estimation algorithms, use of observers