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on a subset of the participating devices. Aggregate computing provides a unifying foundation for developing these systems, avoiding a centralised server and obtaining deployment on multiple hardware
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will be validated through scaled hardware‑in‑the‑loop (HIL) laboratory experiments. Collaboration within the FME SOLAR consortium is an integral part of the position. Required qualifications Master’s
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) for Future Distribution Networks. The position is for a period of three years. The objective of the position is to complete research training to the level of a doctoral degree. Admission to the PhD programme
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environment in Norway, and offer a wide range of theoretical and applied IT programmes of study at all levels. Our subject areas include hardware, algorithms, visual computing, AI, databases, software
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UiO/Anders Lien 2nd August 2026 Languages English English English PhD Research Fellow in High-Performance Computing Apply for this job See advertisement About the position Position as PhD Research
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communication in parallel/distributed AI/ML Enhancement of AI/ML with in-network computing & processing Adaptation & optimization of AI/ML software libraries for non-conventional hardware architectures Physics
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optimization strategies, including reinforcement learning (RL) and optimal control approaches for state preparation and measurement protocol design under hardware constraints. Develop open-source software and
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to the theoretical development, numerical simulation, and potential hardware-mapping of these oscillator-based systems, exploring concepts like quantum annealing, symmetry breaking, and reservoir computing
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to the theoretical development, numerical simulation, and potential hardware-mapping of these oscillator-based systems, exploring concepts like quantum annealing, symmetry breaking, and reservoir computing