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high resolution national, regional and global demographic estimates. They will explore, test and validate novel statistical and AI methods, working with partners from governments and UN agencies to big
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findings at international conferences. Required qualifications and experience: To succeed, you will hold a PhD (or be close to completion) in Computer Science, Applied Mathematics/Statistics, Physics
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diagnostics and build your growing research profile. Collaborate closely across disciplines, including genomics, clinical medicine, statistics, software engineering, and compute infrastructure to co‑create
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data assembly, software interfacing, test design, statistical analysis, and results reporting. The role will also involve planning and managing project activities, building research skills and networks
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component disciplines; in explainable multi-modal deep learning models, in causal statistical models and in human-machine teaming and AI ethics. The researcher will conduct internationally-leading research in
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deep learning models, in causal statistical models and in human-machine teaming and AI ethics. The researcher will conduct internationally-leading research in human factors with applications
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statistical techniques. Applicants should be fluent in Python, experienced with modern machine learning frameworks such as PyTorch or TensorFlow, and comfortable working with large, complex climate datasets in
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, generative models, or equation discovery — rather than traditional statistical techniques. Applicants should be fluent in Python, experienced with modern machine learning frameworks such as PyTorch