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the development and implementation of machine learning (ML), computer vision (CV), large language models (LLMs), and vision-language models (VLM) to automate data extraction and interpretation for productivity
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University explores synergies between nonlinear control theory and physics informed machine learning to provide formal guarantees on performance, safety, and robustness of robotic and learning-enabled systems
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. The experience can be in any health condition or health service. The role is based in the Health and Care Research Unit in the School of Medicine and Population Health at the University of Sheffield. In this unit
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patient samples. The Sheffield arm of the project will develop statistical and machine learning models to identify and validate predictive biomarkers of resistance evolution in Pseudomonas aeruginosa lung
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the following areas: Machine Learning/AI, Internet of Things technologies. For further information, please contact Prof Gyu Myoung Lee G.M.Lee@ljmu.ac.uk . In return, we offer an excellent benefits package
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adapt advanced machine learning frameworks (SPARKS and CEBRA) for supervised and unsupervised analysis of high-dimensional neural data to decode multisensory information Investigate how neural
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findings and stakeholder insights into accessible, evidence-based resources that support collaborative learning, knowledge exchange, and action. Document research outputs, including analysis and
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other forms of collegiality appropriate to the career stage. Any further enquiries on this post may be directed to Dr Grigorios Kotronoulas, Grigorios.Kotronoulas@glasgow.ac.uk Terms and Conditions Salary
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5 Oct 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position
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+to+apply#Howtoapply-Eligibility) a Master’s degree in Artificial Intelligence, Machine Learning, Computer Science, Cognitive Science, Psychology or a related field excellent knowledge in AI and at least one