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to anthropogenic climate change. Nevertheless, these extreme events may be modulated by large-scale climate variability modes across a wide range of spatial and temporal scales. Using large ensemble multi-model
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) and spatial Machine Learning (ML) models Salary and full employee benefits are offered in accordance with Princeton University guidelines. The Term of appointment is based on rank. Positions
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for preprocessing, integration, and modeling of heterogeneous data (spatial, temporal, tabular) -Conduct research in explainable AI and uncertainty quantification applied to agronomic decisions. -Collaborate with
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-processing pipeline for high-field MRI medical data (normalization, denoising, spatial registration) to optimize the quality and consistency of data used in analyses, and to facilitate the search
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Is the Job related to staff position within a Research Infrastructure? No Offer Description The Role Applications are invited for a Postdoctoral Research Associate in the field of agent-based modelling
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for predictive and prescriptive urban data analysis. Experience in visualizing and analyzing spatial and functional interactions within urban infrastructure. Personal and Organizational Skills Ability to model
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Copernicus Hyperspectral Imaging Mission for the Environment (CHIME). The goal is to explore how CHIME’s rich spectral capabilities, when combined with disruptive technologies such as foundation models
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Google Earth Engin, R, Python, and STAN (e.g., deep learning, Bayesian regression models, spatial analyses), and running analyses on a high-performance computing cluster. Demonstrated record of publishing
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of techniques for countering information maneuvers, differences in online harms and influence campaigns across countries, geo-spatial differences in online harms. Successful applicants will need experience in
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% FTE) postdoctoral scholar with expertise in fire modeling and remotely sensed data to support innovative research. This project will improve our understanding of the conditions under which fuel