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of Oslo. via Unsplash Main responsibilities The position is fully embedded (100%) within SmartForest. The main responsibilities include: Developing supervised deep learning algorithms for 3D laser data
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supervised deep learning algorithms for 3D laser data from forests Developing self-supervised deep learning algorithms for 3D laser data from forests Expand for a wider variety of downstream tasks focused
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page to watch video, or click here to open video) About the position The research focus of this position will be on anomaly detection. We mainly aim to develop methods that are applicable for static and
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university, the internationally accredited registrar and classification society DNV, and Cancer Registry of Norway. You will be analyzing and developing algorithms for privacy preserving health registry data
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are differentially private algorithms for statistical model parameter estimation under different trust relations. About the project The position is funded by the Norwegian Research Center for AI Innovation and will be
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classical methods, thereby enabling more efficient solutions. Over the past 25 years, rapid advances—especially the demonstration of quantum algorithms that challenge the extended Church-Turing thesis—have
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that gives you the opportunity to develop a strong profile as researcher. You will also gain valuable experience that might be relevant for your further career. Large language models (LLMs) are today a central
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at SLATE. The position is for a fixed term of four years, with the inclusion of career development work (e.g., teaching, project work) accounting for 25% of the entire period, and is financed by University
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Trondheim, Norway, but the Researcher-project is of both academic and industrial relevance, and it will therefore be developed in close cooperation between NTNU in Trondheim and the company Petronas, which is
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of career development work (e.g., teaching, project work) accounting for 25% of the entire period, and is financed by University of Bergen. The position is open to an incoming candidate, se LEAD AI mobility