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England. Attracting and retaining high-calibre people is fundamental to our continued success. The Role Are you interested in applying machine learning and computational methods to address real-world
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%) allocated to teaching on the School’s programmes and developing the Alfred Landecker Programme. The post is generously supported by funds from the Alfred Landecker Foundation, to support a programme of
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We have an opportunity for a Research Assistant to contribute to a programme of research, RIPPLE, led by Dr. Beatriz Goulao and aiming to improve the sustainability of the health services by
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, meaning that familiarity with one or more cloud-based platforms such as Google Earth Engine, Microsoft Planetary Computer and/or Amazon Web Server/similar is essential. It will also involve the development
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Research Assistant to investigate digital reading comprehension through large-scale data analysis. This role, funded by the John Fell Fund, sits at the fascinating intersection of computational
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: Computational materials modeling: DFT, molecular dynamics, phase-field modeling, or multiscale simulations. Data-driven materials discovery: ML models for property prediction, materials design, or synthesis
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to reduce inequality in high-income countries, and/or (3) the study of social mobility and its relationship to economic inequality. The post holder will work with the INET Oxford programme on Economics
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safety. Be supervised by Lab Managers/Scientists. Be involved in scientific portfolio, including publications, projects or conferences. Before submitting your application please ensure you read the Job
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process simulation, techno-economic analysis (TEA), and life cycle assessment (LCA) methodologies Strong computational skills, including proven expertise in programming environments (e.g., Python, Matlab
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preceding the start date of the research degree programme. Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a