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is developing research excellence in areas including Machine Learning, Big Data, Visual Analytics, Computational Intelligence, Machine Learning, Software Implementation and Testing, and their
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, fabrication materials and orbital environments. Using a small number of representative test cases, we will trial Machine Learning-based predictive methods to estimate material condition and indicative reuse
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individuals participating in studies investigating the cardiovascular consequences of preterm birth. By combining fluid dynamics, machine learning, and advanced imaging analysis, the project seeks to develop
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, with opportunities to lead analyses, develop new expertise and contribute to high-impact scientific publications, and must have: A PhD, or equivalent research experience, in computer sciences
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adaptive cybersecurity solutions for shared social and economic systems. The successful researcher will apply expertise in programmable networking, network traffic analysis, and machine-learning
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, clinical and sensor data processing, quantitative image analysis and machine learning. They will establish and maintain robust research databases and FAIR-compliant data management processes for large, multi
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machine-learning, predictive-modelling or multivariate methods to behavioural and/or EEG data. Proficiency in R, MATLAB and Python. What we can offer In return we offer a generous pension, relocation
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demonstrate experience in animal behaviour research, ideally in aquatic species, together with practical skills in video-based behavioural analysis and/or applying computer vision or machine learning methods
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, clinical and sensor data processing, quantitative image analysis and machine learning. They will establish and maintain robust research databases and FAIR-compliant data management processes for large, multi
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proving, machine learning for reasoning, or neurosymbolic AI. Desirable Application/interview Further Information Grade Grade 8 Salary £48,822 - £51,753 Work arrangement Full-time Duration Until 30th