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and data-driven manufacturing. We are seeking a highly motivated Machine Learning Researcher to join a multidisciplinary team of fabrication engineers and AI specialists at the University of Southampton
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, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage. Machine Learning Expertise: Familiarity with causal machine learning, ensemble methods, and deep learning
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close to completing their qualification. They should have experience in systems engineering, simulation, digital modelling, machine learning, artificial intelligence, or digital twin (model, shadow, twin
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would have a background in machine learning, manufacturing, characterization, and testing of novel high performance multifunctional materials. During the project, you will conduct independent research
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, organised researcher who can evidence: A PhD, or equivalent in statistics, machine learning or a closely related discipline, OR near to completion of a PhD. Expert knowledge of statistical inference methods
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of Aberdeen to work on a project “Predicting Response in Triple Negative Breast Cancer Using Machine Learning”. We seek to appoint a creative and motivated individual to use machine learning (ML) to identify
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combined with human support. To learn more please visit https://www.kcl.ac.uk/research/embrace About the role The Research Fellow in Digital Health & Data Sciences is focused on the development and
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(R2) Positions PhD Positions Application Deadline 26 Apr 2026 - 23:59 (Europe/London) Country United Kingdom Type of Contract Temporary Job Status Full-time Hours Per Week 37 Is the job funded through
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or machine learning. Excellent programming skills in Python and deep learning frameworks A collaborative mindset and interest in socially impactful research. Experience with sign language data, multimodal
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digital health Computing systems and networks Cybersecurity Human-computer interaction Machine learning and artificial intelligence Software engineering Position details Positions are intended