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and machine learning algorithms to analyse and interpret the acquired data. The successful candidate will work primarily with Dr Qimei Zhang in the Department of Engineering at the Nottingham Trent
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analysis, or assistive technology; Experience in applying AI methods such as machine learning, deep learning, computer vision, multimodal data analysis and large language models (LLM) in health-related
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problems, numerical mathematics, optimisation, machine learning and imaging physics, with applications ranging from medical and industrial imaging to geophysics. For more information, please visit
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, and machine learning methods, choosing the approach that best fits the scientific question. Investigate systematically what information is contained in imaging data, how it can be extracted, and how
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and apply AI and machine learning methods for signal processing, image analysis, data fusion, and prediction; · build physics-informed and hybrid AI models that combine geophysical knowledge with data
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Advance the theoretical foundations of machine learning, publish in premier venues and help shape the next generation of AI research. · Annual salary package: $104,481 (ACA Level A.4) - $112,550
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processing, machine learning, computational imaging, and clinical translation. Beyond your individual research contributions, you will serve as a technical coach for the PhD researchers, helping to align
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statistical and machine learning, deep learning, chemometrics, multimodal data fusion, computer vision, uncertainty-aware modeling, stochastic control, optimization, and deployable edge-to-cloud decision
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-resolution or single-molecule imaging. ● Experience with machine learning/deep learning for bioimage analysis, including model application, validation and/or development. ● Experience with optical development
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working towards a shared goal. You will be responsible for the design and pilot testing of machine learning-based automated ultrasound video analysis models that incorporate temporal reasoning. The research