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sheet evolution, methane hydrate fluxes, or applying machine learning to geosciences to reconstruct glacial histories and project future ice sheet behavior. Please read this interview for more details
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developed countries, smartphone penetration exceeds 80%. The automatic transport mode detection (TMD), when effectively exploited, possibly using some kind of machine learning algorithm, provides more
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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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Environment Convergence Environment. Clim-SHOCK investigates volcanic climate shocks from the past and places them into a future scenario. What can we learn from the past to improve future climate projections
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questions and data of CREATE. The successful candidate will conduct advanced methodological and psychometric research. Potential topics include (a) AI, machine learning, and large language models
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processes based on mobile digital technologies increase, so do the amount and severity of cyber threats. Both defenders and attackers are now using Machine Learning (ML) and Artificial Intelligence (AI
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) to enhance AML capabilities. AI-driven solutions can learn from vast datasets to spot hidden patterns and anomalies beyond human or rule-based detection. For more information and how to apply: https
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, NTNU will arrange for you to acquire such competence during the employment period. In such cases, you will also be assigned relevant teaching as part of the career-promoting work. The appointment is to
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UiO/Anders Lien 8th March 2026 Languages English English English PhD Research Fellow in Machine Learning and Statistics Apply for this job See advertisement About the position Integreat
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the Atmosphere for Investigation and Learning”), Maria Skłodowska Curie Actions (MSCA) Doctoral Network funded by the Horizon Europe programme. About the project/work tasks: Thunderclouds are the most energetic