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, and looking for a PhD position, this opportunity can be for you. The Energy Informatics EI@ND Networks and Distributed Systems group at the Department of Informatics (IFI), University of Oslo (UiO) is
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-using models, retrieval systems, or related AI systems Experience with large-scale datasets, distributed training, or high-performance computing environments Interest in scientific applications of AI
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language models in distributed environments while safeguarding both model integrity and data confidentiality. The successful candidate will develop novel frameworks that enable effective collaboration
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maintained across a distributed, multi-site, multi-company construction programme. Through close collaboration with industrial and organisational partners, you will build a research profile combining
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to enable distributed clients (e.g., mobile devices) to jointly train a machine learning model without pooling their raw data into a centralised server. Because data never leaves from user clients
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for reproducible, efficient and scalable training and inference on parallel, distributed and GPU-accelerated computing systems Benchmark the developed approaches against established methods, assessing
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DECIDE research team. DECIDE conducts cutting-edge research on Distributed and Embodied Computing in Dynamic Environments. The team works to realize a vision where humans and robots cooperate
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across diverse populations and biobanks for risk prediction, genetic discovery, and genomic medicine. Federated and transfer learning for distributed and privacy-preserving data integration. AI and Deep
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, or by connecting multiple sensors into distributed quantum sensing networks. Understanding the interplay between these mechanisms, particularly in the presence of noise and decoherence, remains an
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buildings Development of strategies for distributed localization and orientation (e.g. sensor fusion, RTLS integration) Implementation of a prototype for coordinating multiple agents/robots in a