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Field
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Dipartimento di Ingegneria dell'Informazione - Università degli studi di Padova | Italy | 2 months ago
tasks include: (i) developing federated data profiling and quality estimation algorithms that operate without centralizing sensitive health data; (ii) designing quality-aware aggregation strategies
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. We develop novel optimization methods, Machine Learning algorithms, and prototypical Energy Management systems (EMS) controlling complex energy systems like buildings, electricity distribution grids
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Dipartimento di Ingegneria dell'Informazione - Università degli studi di Padova | Italy | 2 months ago
. The proposed project aims to develop new techniques for observability analysis and distributed state estimation directly from data, even in the presence of noise, disturbances, and unmeasured inputs
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, radio resource management, network slicing, traffic steering, and distributed orchestration across multiple clouds and network domains. The successful applicant will conduct research on learning-driven
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Centar izvrsnosti MARBLE drustvo s ogranicenom odgovornoscu za istrazivanje i razvoj | Croatia | 13 days ago
for robotic planning and control Distributed and decentralised coordination and decision-making for multi-robot systems Communication-aware and connectivity-constrained multi-robot coordination Adaptive mission
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performance, and data and product quality. You will join the section in charge of sensor performance, data quality, algorithm development, and calibration and validation (Cal/Val) for the ESA EO missions
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cancer cohorts. • Proven ability to develop novel computational and AI-driven methodologies, including Bayesian generative models, phylogenetic inference tools, and algorithms for multimodal data
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develop advanced models, algorithms, and control solutions for simulating, optimizing, and operating future integrated energy systems. We address the challenges arising from the increasing integration
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networking, distributed quantum computing, quantum-system architectures, or closely related areas. Develop models, algorithms, simulation capabilities, and research software for the design and evaluation
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. These differences introduce distribution shifts that can degrade model performance and reliability over time, particularly in “one-to-many” supervision settings where a single human operator oversees multiple agents