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Field
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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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at industry-facing events. Strong technical and scientific knowledge in machine learning, preferably with experience in large language models (LLMs). Solid foundations in mathematics and engineering
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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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-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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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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oscillations and BSM processes. This will involve taking a lead role in developing dedicated software frameworks, including the implementation of machine learning techniques. Ultimately, the software will be
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, Nutritional Sciences and Women's Health cluster) for REF was rated as world-leading or internationally excellent. We use this expertise to teach the next generation of health professionals and research
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an array of relevant teaching topics Enthusiasm to participating in both curricular and extracurricular activities Subject areas of particular interest may include: Machine and Deep Learning Data
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contexts. They will be expected to contribute to the effective delivery of teaching, learning, and student support by: Delivering and evaluating classroom and practical teaching across modules Designing and