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photovoltaic generation, hydrogen production, and storage alternatives with microgrid-driven power distribution. Through advanced modelling and optimization techniques, this research aims to identify optimum
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. Applications are invited for a full-time Research Assistant in Computer Vision and Machine Learning (Visual-AI) with a particular emphasis on deep learning for anomaly and out of distribution detection. The post
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on developing new generative modeling approaches, scalable training algorithms, and foundation model technologies. The role is suited for candidates with a strong machine learning background who are excited
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) until 31 March 2027 (with the possibility of an extension). The appointed candidate will support advanced research initiatives focusing on systems design, distributed systems, and algorithmic optimisation
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, physical AI, and spatial AI. The RF will contribute to the development of innovative algorithms, data preparation pipelines, and experimental evaluations that are central to the Physical Vision Group’s long
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to architectures, algorithms, and applications. Titled "Exploring Atomic Ensemble Qubits for Distributed Quantum Computing," this LBNL-funded initiative brings together experts from the ESnet, NERSC, and AMCR
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10th August 2026 Languages English English Norsk Nynorsk English PhD Research Fellow in Algorithms Apply for this job See advertisement UiB - Knowledge that shapes society UiB shall be among
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supply chain processes, including transport operations, fleet management, and operational readiness frameworks Model & Algorithm Development: Design, build and implement optimisation models for various
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distribution, and smart-grid applications. The Research Fellow will contribute to project execution, research proposal preparation, industry collaboration, and the dissemination of research outcomes through
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synergistically integrates different renewable energy sources such as solar photovoltaic generation, hydrogen production, and storage alternatives with microgrid-driven power distribution. Through advanced