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collaboration with national and international development partners. Collect and analyse data from fieldwork and desktop research Develop and maintain global stakeholder networks in poverty and sustainability
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: Developing and deploying machine learning models (e.g. graph neural networks, neural force fields, diffusion models) for molecular property prediction and molecular generation. Integrating quantum chemistry
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criteria A PhD in Computer Science or Software Engineering or Computational Statistics, or a related field; or a Master’s qualification in a relevant field and/or equivalent demonstrated experience
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fully resolved single-fracture simulations to large-scale discrete fracture network (DFN) upscaling. Your work will directly address high-value industry challenges in energy and resource systems. CML is
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delivery and education provide informal mentorship to junior researchers and contribute to a collaborative and inclusive research culture actively participate in professional networks contributing
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institutions, including Politecnico di Torino, to advance scientific understanding and drive innovation through agent-based models, population models, and software implementations. This unique opportunity allows
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or research institution. Benefits The Net Annual Income of the fund is to be used to provide one or more fellowships. Each fellowship is paid in two equal instalments: the first upon acceptance
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sciences, spatial statistics and genetics. Your responsibilities will include but are not limited to: Developing code and using statistical software to manage and analyse data Contributing to the drafting
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research focus areas. The Research Fellow will embed their research expertise into the life of the School through the development of high-quality, productivity driven research networks across RMIT and with
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(Japanese-based staff). Please note for the purposes of this program early career researchers are defined as academic staff who have completed their PhD within the last ten years. South Australian Applicants