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data. Change: The CROPWAVES project will exploit satellite-based products for soil moisture and vegetation using data assimilation to improve global-scale crop and climate models at different resolutions
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successful in this role, you will hold (or be close to completing) a PhD/DPhil in machine learning, artificial intelligence, computer science, epidemiology, health data science, or a related quantitative
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water quality, development of synthetic stormwater recipes through in-depth literature review and data mining, monitoring and modeling of stormwater treatment systems, investigation of maintenance and
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of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at the final stages of the selection
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data. Implement, test, document, and maintain research software; integrate trained models with surface-hopping and related nonadiabatic or path-integral workflows and with relevant simulation-code
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smarter recovery? Are you motivated to combine claims data, experiments and risk modelling to contribute to a more resilient built environment in the Netherlands? Are you our new colleague? We are looking
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 11 hours ago
from data science to modeling. This opportunity solicits highly motivated postdoctoral candidates (including final year PhDs) to propose novel and exciting research topics in collaboration with
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. or equivalent doctorate (e.g. Sc.D., M.D., D.V.M.) Preferred Qualifications:. A PhD or MD/PhD (or equivalent) in biological sciences Strong research background in cell biology, molecular biology, mouse models
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, with demonstrated experience in one or more of the following areas: computer vision, markerless pose estimation, movement analysis, behavioural quantification, time-series modelling, or multimodal data
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learning for cardiovascular digital twins and AI-enabled precision treatment. The postholder will develop patient-specific models that integrate multimodal clinical, physiological, imaging and sensor data