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CLIMES Doctoral Network, we are looking for a candidate to use text mining, natural language processing, and large language models to extract, analyse, and spatialise information on the socioeconomic and
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Climate Trends (IMPACT) Post Duration: 18 Months, Whole-Time Salary: €54,850 - €59,654 p.a. (IUA PD2 Scale) For an information package including further details of the post see https://ore.ucc.ie/ Informal
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at the intersection of generative artificial intelligence, climate hazard exposure modeling, and infrastructure risk analysis. New York University (NYU) is one of the top private universities in the United States, and
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of Environmental Engineering, ETH Zürich and matriculate in ETH Zürich. The research is related to development of experimental and modeling techniques to identify emission sources, simulate the airborne transport
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, predict, and manage them remains fragmented across disciplines. The Understanding and Predicting Impacts of Climate Extremes under Global Change Doctoral Network (CLIMES DN) (https://www.climes.se/climesdn
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Center (WERC) in College of Engineering at the University of Texas at Arlington invite applications for a tenure-track Assistant Professor in water resources engineering with an emphasis on modeling-based
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(SustainCARE, https://doi.org/10.3030/101220359 ), led by Dr. Yun Liu. SustainCARE brings together heritage science, building physics, advanced modelling, and climate-conscious preservation, offering a unique
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modeling with SUMO. Programming transport modes with Python. Integration of climate constraints into a transport model. Emergency and disruption management. Where to apply Website https://sede.uvigo.gal
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description With a rapidly changing climate combined with increased use of pesticides, it is imperative to understand
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”): Physics-Guided AI for Climate or Earth System Model Downscaling Global climate and earth system models yield massive simulations at low space-time resolutions and are subject to uncertainties resulting from