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faculty Position Location: Taipei, T'ai-pei, Taiwan [map ] Subject Areas: Modeling & Simulation Climate Change Atmospheric Science Climate Science Appl Deadline: 2026/04/01 04:59 AM UnitedKingdomTime
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Posting Details Position Details Title Postdoctoral Research Scholar - Climate Change Impacts Appointment Status Non-Tenure Track Department IU Bloomington Public & Environmental Affairs Location
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science, environmental engineering, and public health to tackle the region’s most pressing climate–health challenges through cutting-edge research, advanced modelling, and interdisciplinary collaboration
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and improve model performance in simulations of tropical weather and climate), evaluation of simulation results (e.g., TC, MJO, and precipitation patterns, land-atmospheric interactions), analysis
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to develop and investigate riverine matter transport within the scope of Earth System Modelling. The Cluster of Excellence "Climate, Climatic Change, and Society" (CLICCS) investigates climate dynamics and
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ALMA MATER STUDIORUM - UNIVERSITA' DI BOLOGNA - - DIPARTIMENTO DI INGEGNERIA CIVILE, CHIMICA, AMBIENTALE E DEI MATERIALI | Italy | 1 day ago
. Structural optimization and numerical modeling. Where to apply Website http://www.unibo.it Requirements Additional Information Eligibility criteria to apply for research grants fill out the form available
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of using models and observations to study weather and climate processes. You will have knowledge of atmospheric dynamics. You will have evidence of a strong commitment to publishing scientific results
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of observed meteorological elements at all spatial scales. ICV also constitutes an important source of uncertainty in climate model outputs, especially regarding the occurrence of climatic extremes. Furthermore
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, United States of America [map ] Subject Areas: Education / Course Design Climate Change Environmental Studies / Natural Resources Science and Management Environmental Economics, Policy, and Science Development Economics
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the development and application of probabilistic inference methods and machine learning techniques for quantitative uncertainty modeling and for the integration of heterogeneous climate data