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Field
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methodology, theory, and applications across the areas of Bayesian experimental design, active learning, probabilistic deep learning, and related topics. The £1.23M project is funded by the UKRI Horizon
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applications of deep learning, medical imaging, and biomarker integration. This full-time, one-year position offers a unique opportunity to engage in impactful research at the intersection of AI, connectomics
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electronic health records (EHRs) from multiple UK hospital centres using advanced data analytics including machine learning, deep learning, and statistical techniques—with a particular emphasis on deep
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record of publications in reputable peer-reviewed journals or conferences in maritime transport, logistics management, machine learning, deep learning, and optimization; Proficient in written and spoken
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formula. Preferred Qualifications Familiarity with Python, R and MATLAB. Experience with machine learning/deep learning. Master’s degree in a related field. PhD or near to completion of a PhD (or equivalent
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the possibility of yearly renewal subject to funding availability. Responsibilities • Design and implement deep learning architectures, AI agent pipelines, and computer vision algorithms to achieve project goals
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About the Role The combination of personalised biophysical models and deep learning techniques with a digital twin approach has the potential to generate new treatments for cardiac diseases. Our
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About the Role The combination of personalised biophysical models and deep learning techniques with a digital twin approach has the potential to generate new treatments for cardiac diseases. Our
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the WATOC Dirac Medal. As the successful candidate, you will contribute to the design and implementation of AI models that integrate quantum mechanical theory with deep learning, enabling rapid and
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, focusing on high-performance deep learning for neural implicit reconstruction of ultrasound data. The goal is to advance the scalability and efficiency of neural radiance fields (NeRFs) and related