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Field
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will hold a relevant PhD/Dphil in statistics, machine learning or similar area, together with relevant experience working with brain imaging data and possess sufficient specialist knowledge in brain
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Computer Engineering or related areas; Knowledge of the development of automatic [deep] learning and information visualization applications; Experience in the use of algorithms and data analysis methods
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Transactions on Probabilistic Machine Learning. A Gelman, A Vehtari, D Simpson, CC Margossian, B Carpenter, Y Yao, L Kennedy, J Gabry, PC Bürkner, M Modrák (2020). Bayesian Workflow. B Carpenter, A Gelman, MD
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the broader community. You have BS in machine learning, cybersecurity, statistics, or related discipline with eight (8) years of experience; OR MS in the same fields with five (5) years of experience; OR PhD in
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the broader community. You have BS in machine learning, cybersecurity, statistics, or related discipline with ten (10) years of experience; OR MS in the same fields with eight (8) years of experience; OR PhD in
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to support a diverse and inclusive university in which to work, study, teach, research and serve. No person shall be denied employment on the basis of any legally protected status or subjected to prohibited
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in programming (e.g., Python), data analysis, and machine learning, and a curiosity about applying computational methods to diverse domains such as biology, psychology, and medicine. Candidates
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models combining machine learning, and physics-of-failure (PoF) approaches using in-situ data • You work on projects independently • You will present your work at international conferences and
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Europe. In the Monitoring & AI department, you will be involved in the development and implementation of AI and machine learning (ML) tools for monitoring and operation of CO2 storage sites. Key
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the challenge of time-consuming sideshaft testing. As a key member of the team, you will apply cutting-edge machine learning and deep learning techniques to dramatically reduce testing cycles. You will lead life