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Supervisor: Professor Fernanda Duarte Start date: 1st October 2026 Applications are invited for a fully-funded DPhil studentship in Machine Learning Interatomic Potentials for Metal-Ligand
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models, which are essential for understanding climate change impacts. The work involves reviewing existing modeling and model–data fusion techniques, and developing faster, machine-learning–based tools
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this limitation in the use of satellite observations by make a direct use of radiance observations retrieved by satellites using machine learning without the need of radiative transfer calculations. The new model
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in neuroimaging, applied data science and/or machine learning are desirable. Funding & how to apply The scholarship will fund course fees up to the value of home fees*, a tax-free stipend in line with
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into open-source software tools and data portals of the institute • Collaborate with internal and external, as well as national and international, project partners Present your results at national and
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book carts, and assist with physical relocation of books and materials Minimum Requirements: Currently enrolled in the MLIS program Strong written and verbal communication skills Basic computer literacy
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leadership in deploying new tools and strategies for promoting academic freedom and improving respect for university values globally. Information at www.scholarsatrisk.org Job description: Scholars at Risk is
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understanding of enrichment devices using analytical methods and computational tools such as finite element analysis (FEA). The Senior Electric Motor Researcher will provide research and development (R&D
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innovative Emergency Response tools. This work is supported by the Enterprise Ireland Commercialisation Fund Programme through project CF20242528. The project, ‘DeCaMaP’ focuses on providing a comprehensive
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Management Science, Information Systems Research, and MIS Quarterly. We seek applicants with a strong quantitative background, such as analytical modeling, econometrics, and/or machine learning, and a