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Field
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data set (e.g. neutron irradiations, that take years/decades to generate). Digilab brings AI/ML (artificial intelligence / machine learning) approaches for data engineering and automation to utilise
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and data processing skills: experience of programming in one or more languages (e.g. R, C/C++, Python, Matlab). Practical experience of algorithm development and implementation of machine learning
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China invites applications for a Professor / Associate Professor in Econometrics with a strong specialization in Machine Learning and Data Science. The appointment is expected to begin in August 2026
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round Details This project explores how machine learning and artificial intelligence can transform the scholarly digital editing process, not only by potentially automating and enhancing editorial
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BSM processes. This will involve taking a lead role in developing dedicated software frameworks, including the implementation of machine learning techniques. A long-term attachment (6-12 months) and
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snails; (2) assist in developing computational digital twin and machine learning simulations; (3) build and test robotic prototypes; and (4) undertake developmental work including data analysis and paper
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and machine learning models. To be successful in this role, you will have excellent communication skills and written English, strong quantitative and analytical skills, the ability to work creatively
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connectivity and network neuroscience measures? Can machine learning models trained on high-quality clinical data be adapted to work effectively with lower-quality data from community settings? For more
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specialised expertise in the Machine Learning for Engineering sub-theme. Candidates from all areas in machine learning are encouraged to apply, with a special focus on the areas of (i) information theory and
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. The PhD will combine behavioural experiments, machine learning, and explainable-AI methods to answer questions: Do SR techniques improve human face identification accuracy? How do SR-enhanced images affect