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for Catalysis and Organic Chemistry at the Department of Chemistry. The group has extensive experience in computational modelling, reaction mechanisms, and machine learning for catalyst design and discovery. Nova
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accelerated AI, machine learning, and robotics algorithms with a strong focus on computational efficiency, memory reduction, and energy-aware deployment. The role targets foundation models, including large
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communication skills in English (see https://www.mn.uio.no/english/research/phd/regulations/regulations.html#toc8 ) Desired qualifications: Although not being strict requirements, the following qualification
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accelerator design, verification, and physical implementation using open-source tools. Explore architecture-algorithm co-design for machine learning and AI acceleration. Perform performance, power, and area
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to machine learning algorithms in order to get uncertainty estimates for parameters governing the distribution of the observed data. The predictive Bayes scheme for uncertainty quantification contains a wide
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sciences, Applied Mathematics or Physics, and related. Admission Requirements: Candidates must hold a master’s degree in one of the aforementioned scientific areas and be enrolled in a PhD program or in a
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veterinary technician simulation training as well as internal and external continuing education. This experience will provide the foundation necessary to: identify the learning needs of diverse audiences
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of Informatics. You will be part of Visual Intelligence and the DSB group. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/293458/phd-research-fellow-in-deep-learning
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related field Strong background in data analysis, particularly with behavior data, functional ultrasound (fUS) or other neuroimaging modalities Proficiency in statistical analysis, machine learning, and
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Learning for Medical Imaging and Multi-Modal Data in Cancer Research Apply for this job See advertisement About the position Position as PhD Research Fellow in Deep Learning available at the Department