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Field
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to environmental, nutritional, and economic analyses, support the development of new modelling approaches and datasets, and collaborate on high-impact research outputs and publications. You must hold a PhD/DPhil in
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, land-use change, and environmental dynamics. • Design and implement spatial analytics and geospatial modeling approaches to analyze urban environmental processes. • Apply machine learning and
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projects within the CUS related to urban sustainability, environmental monitoring, and urban resilience. Key Duties • Design and implement machine learning and deep learning models for hydrological
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-trained tool on other image sensors and at different mountain sites presents difficulties. Specifically, generalizing a model trained on a specific site to other sites with different environmental
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 9 hours ago
performance, durability, and environmental exposure; developing mechanistic insights into variability and trade-offs; contributing to lifecycle carbon and cost analyses, and assessing material availability
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position within a Research Infrastructure? No Offer Description The project involves the use of models for the hydrological and environmental analysis of watersheds, as well as for assessing the impacts
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Ice and mixed-phase clouds remain a significant challenge for both observational methods and atmospheric modeling. However, recent advances in both areas offer promising opportunities for progress
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2 Apr 2026 Job Information Organisation/Company Ghent University Research Field Biological sciences » Other Economics » Environmental economics Engineering » Chemical engineering Engineering » Other
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at the metropolitan scale • Integration of AI-based learning capabilities to refine all types of models studied • Consideration of environmental aspects in the comparative evaluation (positive impact and modal switch
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implement advanced statistical models, linking species occurrence, movement, and behaviour to environmental drivers. Conduct quantitative analyses of trophic interactions, monitoring data and diet composition