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co-develop a next-generation ocean component for integration into the universal climate model OASIS. We are looking for a candidate with a PhD (or equivalent) in Physical Oceanography, Atmospheric
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quantitative and digital methods, such as descriptive/inferential statistics, data modelling, machine learning (ML), experimental prototyping and technology ideation. A significant degree of autonomy is required
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communication journals Demonstrable proficiency in advanced quantitative data analysis: applied machine learning, statistical analysis, and handling complex data. Programming skills in Python and R are essential
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events. Applicants will possess a relevant PhD or equivalent qualification/experience in a related field of study. The successful applicant will be a nationally recognised authority in invertebrate
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Stipendiary: 4 years fixed term Stipend: £32,428 (with a PhD) or £26,376 (without a PhD) The College invites applications for a stipendiary Junior Research Fellowship in specified areas
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the domain on health and wellbeing. In addition, the post will involve administrative tasks associated with the running of the project and the requirements of our funders. It is essential that you have a PhD
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and other administrative support (pastoral oversight, admissions and learning support) will be under the direction of the Tutorial Fellows. The post-holder will be expected to work in Oxford during
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sources of research funding and contribute to the process of securing funds and make presentations at conferences and other events. Applicants will possess a relevant PhD or equivalent qualification
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science and artificial intelligence concepts and tools to solve complex problems. Candidates will also be developing machine learning techniques and applying them at scale to specific projects with regular
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Essential Qualifications and Experience: PhD (or near completion) in political science, social sciences, public/global health, or related field Strong understanding of climate change and health, particularly