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, working closely with the Core Outcome Measures in Effectiveness Trials (COMET) Initiative. You will develop and evaluate natural language processing and machine-learning methods (including large language
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to have published in leading machine learning conferences or similar venues. One or two PDRAs will be recruited to work within one of, or across, the four research themes: Learning with Structured
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the Computing & Engineering Department. The group is very dynamic, ambitious, well networked and delivers state-of-the-art research in a range of machine learning and data science topics, publishing research
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. machine learning, computer science, mathematics, statistics, physics, theoretical neuroscience or a closely related field) with significant post-qualification research experience. You will experience
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Weather and climate prediction are undergoing a profound transformation. Alongside traditional physics-based forecast systems, machine-learned (ML) weather prediction models, hybrid ML-physics
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, pharmacology, genomics and multi-omics, as well as growing methods in advanced analytics of health data e.g. machine learning to improve human health with a focus on therapeutics. These posts will work alongside
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architecture of entirely new foundation models, directly advancing the frontier of computational biology and machine learning. You will also implement parallel systems capable of training such models across
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, machine learning, governance and operations, we aim to address the complex challenges and opportunities of space exploration CfAI is a large research group in the Department of Physics at Durham University
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development About You You will hold a Ph.D/D.Phil in a quantitative or theoretical discipline (e.g. machine learning, computer science, mathematics, statistics, physics, theoretical neuroscience or a closely
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. Key duties involve driving foundational research and system development in Edge AI and decentralized learning architectures. Responsibilities encompass conducting independent systems-level research