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– The Norwegian Centre for Trustworthy AI ). Qualification requirements The applicants would need to have PhD in either; learning sciences, educational sciences, educational psychology or human-computer
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of deep neural networks and AI-enabled systems. Explore techniques such as abstraction, invariant learning, convex approximation, symbolic analysis and high-dimensional geometric analysis to improve
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methods and deep learning to enable scientific reasoning. Develop software prototypes for automated research workflows that integrate autonomous discovery pipelines with modern deep learning architectures
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, multimodal, and agentic AI, as well as foundation models, with a focus on geometric deep learning, large-scale knowledge graphs, and large language models. Fellows will also have the opportunity to apply
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English PhD Research Fellow in Machine Learning and Statistics Apply for this job See advertisement About the position Integreat - the Norwegian Centre for Knowledge-driven Machine Learning
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differential geometry, algebraic geometry, etc.) or for computer science (such as machine learning, linear logic, etc.).While the position start date is flexible, the successful applicant must have completed
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differential geometry, algebraic geometry, etc.) or for computer science (such as machine learning, linear logic, etc.). While the position start date is flexible, the successful applicant must have completed
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. We particularly welcome applicants with strong expertise in Isabelle/HOL or other interactive theorem provers, formal verification and security, or neurosymbolic AI and AI-assisted reasoning. Deep
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access to the University's research resources, working under the mentorship and guidance of Associate Professor Courtney Fung, PhD, and Honorary Professor Bates Gill, PhD. The fellowship is structured
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according to the expertise of the applicant, and there is potential for fieldwork. You will have a PhD (or equivalent) in geoscience, with skills in, or willingness to learn, petrology and pore-scale flow