246 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" research jobs at University of Oslo
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-working candidate. Main responsibilities Develop and apply machine learning and statistical modeling techniques, including novel AI architectures, for the analysis of complex traits and precision prediction
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exemptions from the requirements: https://www.mn.uio.no/english/research/phd/regulations/regulations.html#toc8 Grade requirements: The norm is as follows: The average grade point for courses included in
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the final exam. Desired qualifications: Experience in areas such as machine learning, computer vision, control sys-tems, perception, control engineering, or autonomous systems Familiarity with ROS (Robot
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collaborative EU funded doctoral training network HEALENAE: Health and Environment in Africa and Europe. The network will consist of 15 PhDs, that together will work and learn as an international cohort and
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mediators using in vivo mouse models. The position has a duration of two years. The project group is part of a vibrant and inclusive research environment (https://www.ous-research.no/kt/) at the Department
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experience in computational modelling, reaction mechanisms, and machine learning for catalyst design and discovery. Nova is also a Principal Investigator at the Hylleraas Centre for Quantum Molecular Science
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ADNI studies The position is primarily focused on advanced statistical analysis and data integration. While machine learning and computational approaches may be applied where appropriate, the core
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topics include (a) AI, machine learning, and large language models for measurement challenges (e.g., for small-sample calibration or for accelerated algorithms), (b) identifying and investigating aberrant
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modeling; performing source separation on commercial recordings and extracting audio features (onsets, pitch, harmony, dynamics); curating datasets; and integrating machine learning approaches to complement
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and data integration. While machine learning and computational approaches may be applied where appropriate, the core emphasis of the role is on population-level data analysis, interpretation, and