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Field
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Desirable criteria Experience of advanced statistical and/or machine learning methods, such as longitudinal analysis methods, latent variables models, clustering algorithms, missing data and clinical trial
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social research in sociology such as causal inference or machine learning or complex panel data analysis. We are seeking excellent applicants with an international research portfolio and network
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. Interests could include geological field-based methods and big data applications and machine learning methods. Research focus will be on feedback processes between erosion, sedimentation, tectonics and
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Subject areas of particular interest may include: Machine and Deep Learning Data Visualisation Generative AI and LLMs Programming (Python, R, SQL) Databases and IoT Applied Statistical Methods You will also
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Applicants are invited for the posts of Research Associate or Research Fellow in Machine Learning to work with AI Researchers in the Centre for AI Fundamentals at the University of Manchester. You
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modelling, satellite data assimilation, multivariate statistics, and machine learning. Prior experience with model and satellite products for mapping and understanding SM-dependent hazards (like floods
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: PhD or equivalent degree in Robotics, Computer Science, Machine Learning, AI, Control Engineering, or a related field. Excellent programming skills and experience with related tools and software. A
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centres. At Cambridge, our mission is to contribute to society through world-class education, learning, and research. With a deep respect for tradition and a bold vision for the future, we continue to shape
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-driven solutions that enhance dam safety and energy efficiency amid climate change and ageing infrastructure. The PDRA will work with Dr Simon Moulds on machine learning approaches for reservoir inflow
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are invited for the 2026 Research Fellowship awards. Up to four Research Fellowships will be awarded in this competition. Applicants should have submitted their PhD after 1 October 2024, or be on track