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researcher in natural language processing and large language models to work with a team from multiple disciplines of machine learning and artificial intelligence to develop multimodal large language models
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20th June 2025 Languages English English English PhD Research Fellow in towards battery digitalization: a continuum physics-based model development Apply for this job See advertisement About the
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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on the littoral environment. Algorithm development includes photogrammetric measurements of wave parameters, image stabilization, and use of AI/ML models for image segmentation and classification. Algorithms will
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The Faculty of History and Christ's College invite applications for a three-year fixed term Fellowship, as part of the Isaac Newton Trust's Academic Career Development Fellowship programme. The
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means the thesis must be submitted by the role’s starting date) in a relevant field (e.g. environmental social science, sustainable development, urban design, human geography, community energy). An
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University of Western Sydney | The University Of Sydney, New South Wales | Australia | about 1 month ago
of Superannuation + Leave Loading About The MARCS Institute The MARCS Institute for Brain, Behaviour and Development is an interdisciplinary research institute of Western Sydney University. The vision
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The Faculty of History and Christ's College invite applications for a three-year fixed term Fellowship, as part of the Isaac Newton Trust's Academic Career Development Fellowship programme. The
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with strong expertise and interest in developing porous materials for fertilizer formulation. The position involves the design, synthesis, and characterization of porous materials to control the release
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems