409 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "FORTH" scholarships in United Kingdom
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with NEOM, one of the world’s largest ecological restoration programmes, the project will develop machine-learning approaches to analyse satellite observations of vegetation change and evaluate large
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training programme at the start of the PhD to develop skills in areas such as programming, data analysis, machine learning and signal processing. This will provide the technical foundation required to work
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programming (e.g., Python/C++), machine learning frameworks, or robotics software environments such as ROS. You are motivated to work in a multi-disciplinary research environment combining engineering, AI, and
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language processing, statistical machine learning and causal inference. The scholarship will fund course fees up to the value of home fees*, a tax-free stipend of no less than £20,780 per annum), plus additional
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machine learning and knowledge organisation, for exploring the significant moving image collection at BT Group Archives. This project will be jointly supervised by James Elder and Elspeth Millar( BTGA
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Technology, Digital Media, or related disciplines. You should have some of the following: Strong programming skills (preferably in Python), with experience in machine learning/AI or software engineering for
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machine learning (ML) and artificial intelligence (AI) workflows, the project aims to create a comprehensive molecular atlas and identify novel, translational biomarkers and therapeutic targets. Project
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: machine/deep learning, numerical modelling, statistics, optimisation, scientific computing • Ability to work across disciplines and collaborate with academic and industrial teams Desirable: • Experience in
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: Earth Sciences, Bioscience, Interdisciplinary Life and Environmental Science, Inorganic Materials for Advanced Manufacturing, Chemical Synthesis for a Healthy Planet,Statistics and Statistical Machine
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foundation in either machine learning or mathematical/computational neuroscience, demonstrable programming experience (Python/PyTorch), and the curiosity to work across disciplinary boundaries. A background in