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developing next-generation AI methods for healthy climate adaptation. The position will focus on building and evaluating foundation models for large-scale spatiotemporal health and environmental data. Our team
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. Knowledge of atmospheric science and/or atmospheric modelling. Experience in applying or deriving remote sensing data. Experience in working with climate model data. Experience in teaching at the university
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change, climate change attitudes, and risk under environmental heat stress by combining psychological profiling, biological lab data, physiological time series, and sensor data. The postdoc will play a
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. climate, policy, pollution) on various metrics of land use and biodiversity under different scenarios for the UK. Key Responsibilities include: To develop and adapt a land use and food system modelling tool
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tasks: Develop machine learning and deep learning models for weather and climate (e.g., nowcasting, climate downscaling). Design and follow projects related to AI models for weather and climate Supervise
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, and climate projections depends critically on the adequate representation of land-atmosphere (L-A) feedbacks. These feedbacks are the result of a highly complex network of processes and variables
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Job Title: CAES – Postdoctoral researcher in Modeling and quantitative analysis for efficient use and sustainable management of water at the Farm-Scale in semi-arid regions Job Description
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during orogenesis, contributing to the development of geochemical models and linking these findings to broader tectonic and climatic processes. The role involves managing your own research activities and
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economic factors to enhance urban resilience to water-related challenges. Key Responsibilities Develop models to simulate urban water flows, assess climate change impacts, and test innovative solutions
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, and advanced modelling of metamorphic phase equilibria. You will investigate nitrogen behaviour and isotopic variation during orogenesis, contributing to the development of geochemical models and