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Field
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, data-limited, and dynamically evolving environments. Applications include complex engineered systems such as intelligent communication networks, distributed computing platforms, and quantum-enhanced
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of privacy-preserving artificial intelligence for the benefit of humanity. What You Will Do: Research (Federated Continual Learning): You will develop novel and privacy-preserving algorithms that allow
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? PhD position in Algorithms and Extremal Combinatorics There is a vacancy for a PhD Research Fellow in Algorithms and Extremal Combinatorics at the Department of Informatics . The position is for a fixed
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. SILEX 2025) to calculate the Fire Radiative Power (FRP) and compare with satellite observations (VIIRS, SLSTR, FCI). Develop a fire front segmentation algorithm using machine learning techniques (deep
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Description Distribution estimation algorithms for abductive inference (total or partial) in dynamic domains. Structural learning of dynamic Bayesian networks with discrete and continuous variables (parametric
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Development, implementation and experimentation of distribution estimation algorithms in dynamic optimization problems. Where to apply E-mail lauragveiga@fi.upm.es Requirements Research FieldComputer science
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computing. This will include, but is not limited to, the design of distributed quantum algorithms, circuits, and error correction, as well as the interplay between circuit optimization and circuit
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research subject for this position is development of distributed processing strategies and algorithms for Large Intelligent Surfaces, including both joint baseband processing and synchronization across
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will develop novel and privacy-preserving algorithms that allow distributed devices (smartphones, wearables) to learn from new data streams over time (Continual Learning) while collaborating globally
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for machine learning, with research topics ranging from decentralized and federated optimization, adaptive stochastic algorithms, and generalization in deep learning, to robustness, privacy, and security