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- University of Oslo
- NTNU Norwegian University of Science and Technology
- NTNU - Norwegian University of Science and Technology
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Processing and Image Analysis Group, Section for Machine Learning, Department of Informatics. You will be part of Visual Intelligence and the DSB group. For more information about the position see https
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of a vestibular-inspired neuromorphic microchip (VEST-CHIP) designed for real-time, ultra-low-power bilateral sensor processing to enable continuous monitoring in wearable — and potentially implantable
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to create knowledge for a better world. You will find more information about working at NTNU and the application process here. About the position The Department of Civil and Environmental Engineering (IBM
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special cases within the broader GDL paradigm. Research in GDL relies on a strong theoretical foundation, drawing on group theory, differential geometry, and representation theory. The performance gains
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, 9,000 employees and 43,000 students work to create knowledge for a better world. You will find more information about working at NTNU and the application process here. ... (Video unable to load from
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Science. More about the position Modern diffusion models underpin state-of-the-art generative AI for images and continuous data, yet principled diffusion-based methods for discrete sequences (e.g., DNA, RNA
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data, and MRI brain imaging data from patients with neuropsychiatric and severe mental disorders. In addition, the Centre actively collaborates with major international consortia, including
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Council of Norway to study the role of striatal interneurons in action selection. The basal ganglia play a critical role in decision making. Our aim is to investigate this decision-making process, using a
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novel, modular statistical solvers to integrate domain-specific knowledge directly into latent variable models. Account for spatial structures, physical laws, high-dimensional imaging, and clinical
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inventories and provision of environmental information. Similarly, the developments in AI and machine learning allow for new and improved processing of remotely sensed data supporting precision forestry