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experiments and cognitive modelling. You will focus on machine learning, but will be involved in all areas. There are also spinout opportunities. For details: PhD information sheet The team have wide experience
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species, and the emergence of previously unseen classes. Recent advances in remote sensing and machine learning provide new opportunities to address these challenges, but most current approaches
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collaboration experience. Main duties and responsibilities Develop findable, accessible, interoperable, and reusable (FAIR) AI / machine learning software, tools, and workflows to support multiple exploratory
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on machine learning for NLP, with applications in education, creativity, healthcare, social media, and finance. She specialises in educational NLP, EdTech, language acquisition, multilingual and low-resource
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chemistry, machine learning, movement ecology, RF-engineering, electronics etc). Main duties and responsibilities Devise, develop and test fabrication approaches for the construction of microbatteries in a
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foundations, combining ultrasonic guided wave monitoring, high-fidelity finite element simulations, Bayesian inference, and machine learning. Guided waves can propagate over long distances and reach areas
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(Python, C++). - Knowledge of AI, machine learning, control systems, or reinforcement learning. - Ability to work independently, communicate effectively, and contribute to collaborative research. Desirable
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develop statistical and machine learning models to identify and validate predictive biomarkers of resistance evolution in Pseudomonas aeruginosa lung infection. As part of this work, the postholder will
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data acquisition. • Computational techniques, including machine learning and statistical inference. • Collaborative research at the interface of mathematics, biology, and physics. Why us? The
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physical systems. You will explore how the dynamic behaviour of nanomagnetic devices can be used to realise these KAN functions directly in hardware. Working with a combination of modelling, machine learning