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Field
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simultaneously provide reliable wireless connectivity and high-precision sensing. The objective is to develop localisation and sensing algorithms that achieve near-GNSS accuracy while improving robustness, energy
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scheduling algorithms for fast control and reconfiguration of the optical AI compute clusters. Realize a small-scale compute cluster lab testbed to demonstrate and evaluate the performance of the innovative
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structure-preserving algorithms to generative modeling in AI. It will build upon the work done at IMF and SINTEF in this field. We will consider techniques like flow matching, and use ideas from optimal
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of theoretical and applied IT programmes of study at all levels. Our subject areas include hardware, algorithms, visual computing, AI, databases, software engineering, information systems, learning
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support. The PhD candidate will develop and validate a hybrid methodology that combines established stochastic optimization with AI-based learning. The aim is not only to develop new algorithms, but also to
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and algorithmic framework to assess and improve the resilience of FL-enabled autonomous systems under such heterogeneity, explicitly incorporating the human in the loop. The project will draw
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Computer science » Modelling tools Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 1 Oct 2026 - 23:59 (Europe/Oslo) Country Norway Type of Contract Temporary Job Status
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actuation, feedback and computation across their soft bodies, blurring the boundary between material and machine. Our work hints that key platforms to capture such material intelligence are ‘robotic materials
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2 Jul 2026 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Computer science » Cybernetics Computer science » Programming Engineering » Industrial
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, tiered online prevention programme for adolescents and young adults. SAMPO combines e-screening, personalised e-assessment based on network analyses, and modular online risk and resilience toolboxes. We