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), (c) estimation methods for latent variable models (e.g., two-step approaches or approximate maximum likelihood estimation), or (d) meta-analytic models to address complex data structures (e.g., spatial
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cooperation with the Institute of Marine Research. The core of the position will be on development of new deep learning methods for segmentation/classification of data with limited and weak labels. Your may
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., probability, analysis), eager to conduct cutting edge research in the field of uncertainty quantification, in particular the theory and methods known as predictive Bayes. Predictive Bayes theory involves
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The position An exciting postdoctoral position in method development for spatio-temporal medical data is available in the UiT Machine Learning Group at the Department of Physics and Technology . Goal: Develop
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is also a Principal Investigator at the Hylleraas Centre for Quantum Molecular Science, a Norwegian Centre of Excellence dedicated to the development and application of advanced computer simulations
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statistics. We are looking for a motivated candidate, with a deep interest in mathematical statistics, with a view towards developing new methods for uncertainty quantification. Starting date no later than
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registries, advanced analytical methods, and clinical trial data to inform regulatory decisions, clinical practice, and public health. Read more about UIO:RWE here: https://www.uio.no/english/research
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large datasets analyses Active participation in LALP Lab activities Required selection criteria You must have completed a doctoral degree in cognitive science or computer design/programming Training and
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-, Master's- and PhD degrees. If you have not yet completed your PhD, you must provide confirmation on your estimated date for the doctoral dissertation, or confirmation that your PhD thesis has been submitted
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of Oslo's vibrant team as a PhD Research Fellow in AI methods for innovative robotics! PhD Research Fellow in AI methods for robotic body-brain co-design Apply for this job See advertisement About the