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Field
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The continuous release of Earth Observation (satellite) data and the emergence of Machine Learning methods open up new possibilities for understanding forests. These large datasets provide
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Machine Learning within the School of Medicine at the University of Limerick. This is a methodologically focused PhD for candidates with strong quantitative backgrounds who wish to develop novel statistical
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and large models, limiting real-world deployment. This PhD focuses on efficient Physical AI, emphasising data-efficient training, reinforcement learning, continual adaptation and edge deployment
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machine learning and AI methods to develop clinical decision support systems for high-flow nasal cannula therapy. The project: Concerns around the possible negative consequences of delayed escalation
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and (2) develop learning rules that are both technology-feasible and well-suited for machine-learning workloads. The project will consist among others of the following tasks: Investigate and design
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About the project: Machine learning accelerated electronic transport calculations for complex materials Supervisor: Prof. Neophytos Neophytou, University of Warwick Advancements in materials
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one or more of the following areas is meriting: Bayesian statistics, mathematical modelling, probabilistic machine learning, deep learning, large language models. Rules governing PhD students are set
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29th June 2026 Languages English English English The Department of Mechanical and Industrial Engineering has a vacancy for a PhD Candidate in Machine Learning Approaches to Conservation Condition
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applied mathematical modelling machine learning multi-fidelity modelling numerical methods. Demonstrated programming ability (MATLAB/Python/C++) and enthusiasm to learn PyTorch. Previous experience in one
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PhD Scholarship Opportunity - Processing intelligence for green metals using in situ X-ray characterisation and machine learning Job No.: 693787 Location: Clayton campus Employment Type: Full-time