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Field
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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
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related definitions. Knowledge of SOTA federated learning algorithms. Knowledge of distributed optimization and consensus algorithms. Knowledge of large models and hyper-parameter optimization. Knowledge
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About the Opportunity The Postdoctoral Research Associate advances research in mathematical modeling, optimization, and stochastic analysis for large-scale and distributed systems. The role focuses
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participation in several European and Dutch national projects. Our key research areas include ultra-reliable low latency communications, resource allocation, digital twins, distributed massive MIMO and flexible
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systems. Responsibilities include: Integration of advanced sensing technologies with continuum robotic systems and development of associated sensing and estimation algorithms Path planning based on medical
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strategy; participate in internal research sprints to explore, test and validate novel EO concepts, algorithms and workflows in a fast-paced, collaborative environment; engage with the innovation ecosystem
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AI Algorithm and Autonomous Decision-Making Systems RESPONSIBILITIES Research and develop autonomous decision-making algorithms for process industries (e.g., chemical, pharmaceutical, materials
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algorithms for critical equipment (e.g., compressors, reaction kettles). Research advanced process control strategies and deploy them on the center's distributed control systems and edge computing devices