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, with interests spanning a broad range of areas - including statistical machine learning, high-dimensional data and big data, computationally intensive inference for complex models, causal inference and
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at https://cbu.w.uib.no/joshi-group/ . Co-supervisors include experts in machine learning and AI, Pekka Parviainen and Tom Michoel, alongside leading epidemiologists, Tone Bjørge and Kari Klungsøyr. The core
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Science) in a uniquely interdisciplinary environment. The project will be supervised primarily by Professor Anagha Madhusudan Joshi-Michoel, who specializes in applying machine learning and data science
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of cancer; probabilistic modelling and Bayesian inference, stochastic algorithms and simulation-based inference; and statistical machine learning. More about the position The position is part of the project
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of machine learning (ML) techniques and density functional theory (DFT) simulations as well as experimental validation. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job
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equations (PDEs). The research encompasses both deterministic PDEs and equations subject to stochastic perturbations, integrating approaches from machine learning algorithms, transport theory, and
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synthetic steps (and routes), using machine learning in closed-loop (autonomous) optimizations. The tasks will be varied, and you will have the opportunity to contribute to developing new solutions in a
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Postdoctoral Research Fellow in machine learning for gene therapy Apply for this job See advertisement About the position A three-year position as Postdoctoral Research Fellow in machine learning for gene
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involve close collaboration between molecular biologists, neuroscientists and machine learning experts in our research group as well as with collaborators at e.g. Harvard University and University
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real world applications. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/274371/phd-research-fellow-in-deep-learning-on-image-data-for-subsurface-imaging Where