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Field
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manufacturing, mechatronics, innovative design, nanotechnology, and biomedical and computational applications. Key Responsibilities: The research fellow will be leading the development of AI-based decision-making
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in at any time. Background The School of Mathematics welcomes applications for a research fellowship in statistics to work on the UKRI Future Leaders Fellowship project ‘Computational Statistics
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problems in the health sciences, including fields such as healthcare informatics, movement and rehabilitation sciences, medical imaging, remote sensing, computer vision, mental health, data fusion
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(CPS) for aquaculture, to sensors and platforms for maritime applications. The Postdoc’s primary task will be to lead the development of algorithm, software, and hardware to extend the current HAUCS
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the advances in battery technology, as it enables more precise monitoring, control, and optimization of battery performance throughout its lifecycle. By incorporating digital tools such as algorithms, and
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real-time, and will be tested and demonstrated on a state-of-the-art HiL rig and an autonomous test vehicle. The post is focused on the development of automotive-grade algorithms and estimators that will
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models using frameworks such as PyTorch and TensorFlow. Research experience in medical image analysis using deep learning algorithms. Strong track record in machine learning, computer vision, and medical
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ethical and security standards. Concept and Algorithm Development: Innovate in data science, machine learning, and AI. Data Analysis and Reporting: Contribute to data analysis, reporting, and publication
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algorithms might support the wider integration of, and uptake of, renewable energy technologies for particular use cases and considering a variety of perspectives (technical/policy/social/economic). You will
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grant, have worked to identify the sampling algorithm used by the brain, to show how the identified sampling algorithm can systematically generate classic probabilistic reasoning errors in individuals