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traditional predictive attempts and limits the availability of training data for high-resolution atmospheric and hydrological models. This limitation is compounded by the fact that many atmospheric reanalysis
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and validation of a predictive pipeline for excipient–biologic interactions Integration of experimental SAXS data with AI-driven structural modeling to predict oligomerization behavior and excipient
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The University of Virginia Department of Mechanical and Aerospace Engineering invites applications for a Postdoctoral Research Associate focused on structure design to address critical healthcare
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: The Smart Manufacturing & AI Systems Engineer (KTP Associate) will work on: Data acquisition pipelines and IoT sensor integration Building machine learning models for forecasting, optimisation, and automated
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. This project will involve formalising and integrating the contributions of : (i) model-based and data-driven systems engineering (MBSE), (ii) embedded frugal (explainable and robust) AI, and finally (iii
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faculty members, researchers, research engineers/associates, and doctoral students, working across areas recognised in France and internationally, such as spatial modelling and analysis, health and risk
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on satisfying customer-driven needs by co-locating a diverse, highly skilled R&D team that can address all aspects of a particular problem across the full range of technology-readiness levels. KRI headquarters
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15 Jan 2026 Job Information Organisation/Company Empa Research Field Computer science » Other Engineering » Other Mathematics » Applied mathematics Mathematics » Statistics Researcher Profile First
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of urban rivers utilizing hydraulic modeling, cutting edge AI technology and field research. Villanova is a Catholic university sponsored by the Augustinian Order. The University is an equal opportunity
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in the areas of Hydrological and Earth System Modeling and Artificial Intelligence (AI). The successful candidate will have a strong background in computational science, data analysis, and process