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Senior Researcher in Machine Learning and Climate
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comment: The School of Geography and the Environment is seeking a dynamic Senior Researcher to lead cutting-edge research on lethal humidity and excess mortality predictions. This exciting opportunity involves contributing to a pioneering project on lethal humidity and excess mortality predictions. As a Senior Researcher, you will develop an innovative early warning system for deadly humid heatwaves, predicting impacts 1-6 months ahead. You will collaborate with world-leading experts at UNSW, ANU, and Monash University, under the guidance of Professor Louise Slater at Oxford’s Hydro-Climate Extremes Research Group. Your responsibilities will include developing and maintaining open-source scripts to process global climate data, leading the design of a machine learning framework for mortality predictions, and generating actionable forecasts. Additionally, you will contribute to publishing high-impact research, presenting findings at international conferences, and collaborating across institutions, including travel to Monash University. A commitment to academic citizenship and some teaching within the School of Geography and the Environment is also part of the role. This is a unique opportunity to drive forward cutting-edge research at the intersection of climate science and machine learning. This post is fixed-term until February 2027 and offered on a full-time basis. What We Offer As an employer, we genuinely care about our employees’ well-being, and this is reflected in the range of benefits that we offer including: An excellent contributory pension scheme 38 days annual leave A comprehensive range of childcare services Family leave schemes Cycle loan scheme Discounted bus travel and Season Ticket travel loans. All applications must include a CV, Supporting Statement/Cover Letter. For further guidance and support, please visit https://www.jobs.ox.ac.uk/how-to-apply. Any technical questions related to this vacancy can be sent to: recruit@ouce.ox.ac.uk The closing date for app…
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comment: The School of Geography and the Environment is seeking a dynamic Senior Researcher to lead cutting-edge research on lethal humidity and excess mortality predictions. This exciting opportunity involves contributing to a pioneering project on lethal humidity and excess mortality predictions. As a Senior Researcher, you will develop an innovative early warning system for deadly humid heatwaves, predicting impacts 1-6 months ahead. You will collaborate with world-leading experts at UNSW, ANU, and Monash University, under the guidance of Professor Louise Slater at Oxford’s Hydro-Climate Extremes Research Group. Your responsibilities will include developing and maintaining open-source scripts to process global climate data, leading the design of a machine learning framework for mortality predictions, and generating actionable forecasts. Additionally, you will contribute to publishing high-impact research, presenting findings at international conferences, and collaborating across institutions, including travel to Monash University. A commitment to academic citizenship and some teaching within the School of Geography and the Environment is also part of the role. This is a unique opportunity to drive forward cutting-edge research at the intersection of climate science and machine learning. **This post is fixed-term until February 2027 and offered on a full-time basis.** **What We Offer ** As an employer, we genuinely care about our employees’ well-being, and this is reflected in the range of benefits that we offer including: * An excellent contributory pension scheme * 38 days annual leave * A comprehensive range of childcare services * Family leave schemes * Cycle loan scheme * Discounted bus travel and Season Ticket travel loans. **All applications must include a CV, Supporting Statement/Cover Letter. ** For further guidance and support, please visit **https://www.jobs.ox.ac.uk/how-to-apply**. Any technical questions related to this vacancy can be sent to: _ recruit@ouce.o…
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further particulars: 178258 - Senior Researcher Job Description and Person Specification
application opening date: 2025-02-25T09:00:00+00:00
salary: Research Grade 8: £48,235 - £57,255
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value: Job Description _________________________________________________________________________ Summary Job title Senior Researcher in Machine Learning and Climate Division Social Sciences Department School of Geography and the Environment Location South Parks Road, Oxford OX1 3QY Grade and salary Grade 8 - £48,235 - £62,407 Hours Full time Contract type Fixed-term (end date - February 2027) Reporting to Professor Louise Slater Vacancy reference 178258 Applications are particularly welcome and encouraged from women, black, and minority ethnic candidates, who are under-represented in posts in SoGE. SoGE are committed to equality and values diversity. Additional information The School of Geography and the Environment holds an Athena Swan Silver award in recognition of our commitment and success in addressing gender equality. The School of Geography and the Environment is committed to promoting a culture of equality, diversity, and inclusion in the workplace, including the undertaking of appropriate training as opportunities arise and/or when asked to do so The role This position contributes to a project between the University of Oxford, Monash University, the University of New South Wales (UNSW), and the Australian National University (ANU) on lethal humidity and excess mortality predictions. The Researcher will develop and implement an innovative early warning system for deadly humid heat waves from 1-6 months ahead. They will collaborate with other academics at UNSW, ANU, and Monash University to undertake this research. Reporting to Professor Louise Slater, the Researcher will be a member of the Hydro-Climate Extremes Research Group in the School of Geography and the Environment at the University of Oxford. The position will involve travel to Monash University to work with Professor Yuming Guo. Responsibilities • Develop and maintain open-source scripts (e.g. in Python) to retrieve and process global climate and environmental datasets from various sources, including subs…
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