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About This Role The Resource Demand Forecasting Lead will be responsible for managing and forecasting resource needs across multiple functions in our Quantitative Sciences and Development Operations
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motivated the development of Federated Learning (FL) [1,2], a framework for on-device collaborative training of machine learning models. FL algorithms like FedAvg [3] allow clients to train a common global
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slicing. - Develop advanced AI/ML algorithms and data analytics techniques to automate and optimise exposure requests, adapted to available resources and real-time demand. - Propose and
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. Indeed, when multiple sources exist in the vicinity of a same sensing unit, their signatures mix and estimation of individual sources is disturbed by the other co-occurring sources. The aim of the doctoral
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analyzed. The tensor model structure estimated by suitable optimization algorithms, such as that recently developed in [GOU20], will be considered as a starting point. • Exploiting data multimodality and
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national Luxembourg AI Strategy featuring a healthcare flagship A transnational network of competence that includes multiple Max-Planck and Helmholtz institutes in Saarbrücken The opportunity to impact
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, parameter estimation algorithms, and applications of sensing such as localization. Extreme MIMO: beamforming architectures and techniques for massive ultrawideband antenna arrays Gearbox PHY concept: Flexible
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will have the opportunity to investigate innovative solutions using machine learning algorithms and predictive modelling techniques in the context of a collaborative project with Goodyear Luxembourg (one
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challenges, encompassing both fundamental and applied research, from the development of algorithms, tools, and frameworks that advance scientific discovery to methodologies that utilise computational
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Nature Careers | Northern British Columbia Fort Nelson, British Columbia | Canada | about 1 month ago
cultures drive research that reshapes our understanding of the universe and our place within it. SFU researchers explore natural phenomena on multiple scales from the subatomic to the cosmic, from a single