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related field. The ideal candidates will have experience in one or more of the following topics: deep learning for image and point cloud data processing, deep learning for time series data prediction
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have the opportunity to develop independent research aligned with the aims of the ADN lab. Current work focuses on machine learning and multivariate decoding of neuroimaging data to predict subjective
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predictions, investigating the impact of density prediction errors on orbit prediction, assisting with proposal writing, mentoring undergraduate and graduate students in the group and writing journal and
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precision medicine and predict outcomes. The Post Doc will work collaboratively with other research scientists with the same interest and background. Among the key duties of this position are the following
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of neuroimaging data to predict subjective experiences and individual differences, as well as cognitive modeling of decision-making in both lab and realworld settings. Successful candidates will be supported in
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related engineering fields. The candidate should have skills and experiences in at least one of the following areas: 1) advanced data analytics for performance prediction and risk analysis of transportation
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Rutgers Infrastructure Resilience Group. Both groups involve a number of research activities ranging from hydrologic hazard prediction to state-of-art infrastructure mapping, and are supported by various
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experiences in at least one of the following areas: 1) advanced data analytics for performance prediction and risk analysis of transportation infrastructure; 2) network level optimization for transportation
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. The candidates will also have access to several live testbeds deployed in critical facilities and communities for studies related to early flood warning systems, air quality prediction, and security in soft target