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We seek to appoint a Research Associate (postdoctoral scientist) to join the prolific climate/weather/environmental and impact science community at the University of Oxford, that is interested in
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must hold, or be close to completion of a doctoral degree in a relevant field (e.g., data science, geography, environmental science, public health, economics). You will have experience relevant for food
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must hold, or be close to completion of a doctoral degree in a relevant field (e.g., data science, geography, environmental science, public health, economics). You will have experience relevant for food
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career in the area of attribution/causality analysis, extreme environmental events, climate and data science (including statistics and AI/ML tools), epidemiology, ECD, and beyond, as well as to opening a
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collaboration using a systems approach to tackle antimicrobial resistance in the environment—involving a feasibility study and system modelling of environmental AMR in wastewater. You will use data on AMR in
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collaboration using a systems approach to tackle antimicrobial resistance in the environment—involving a feasibility study and system modelling of environmental AMR in wastewater. You will use data on AMR in
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Aalto University is where science and art meet technology and business. We shape a sustainable future by making research breakthroughs in and across our disciplines, sparking the game changers
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Postdoctoral Research Associate in Forest Resilience, Climate Change, and Human Health in the Amazon
, epidemiology, and socio-environmental modelling. To be considered a successful candidate; A PhD degree in Ecology, Biodiversity analyses, Environmental Science, Remote Sensing, Epidemiology, Data Science, or a
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of research methods and techniques to work within established research programmes. Applicants will be able to demonstrate experience conducting field-based ecological or environmental science research
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collaborators (the EuroWISE collective). Work Package 2 (Analysis and Data Management): The PDRA will be responsible for data analysis, interpretation, and write-up using a critical social science approach