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world leader in genomics. The primary mission of the HGSC is actionable translational research across the full spectrum of human health and disease using large-scale genomic data to drive collaborative
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is close. Our cohesive campuses make it easy to meet, work together and exchange knowledge, which promotes a dynamic and open culture. The ongoing societal transformation and large green investments in
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model fairness and model generalizability across multi-institutional electronic health records databases. The researcher will have access to the real-world EHR data from almost 20 sites across
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propagation problems, stochastic partial differential equations, geometric numerical integration, optimization, biomathematics, biostatistics, spatial modeling, Bayesian inference, high-dimensional data, large
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develop innovative solutions based on the analysis of urban data (big data, IoT, GIS) to monitor and improve public health. You will contribute to modeling smart cities with a focus on health and designing
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University of Pennsylvania, Statistics and Data Science Position ID: 3334 -POSTDOC [#25722] Position Title: Position Type: Postdoctoral Position Location: Philadelphia, Pennsylvania 19146
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Classification Title: Postdoctoral Associate Classification Minimum Requirements: A Ph.D. in biomedical informatics, computer science, information science, data science, (bio)-statistics, (applied
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(Compute Data) Efficient at working with large datasets and synthesizing scientific literature Project management Self-motivated and deliverable-oriented Ability to work both independently and as part of
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convolutional neural networks (CNNs) and large language models (LLMs) to analyze retinal and corneal data including visual fields, fundus photographs, optical coherence tomography (OCT) images and genetics data
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that connect animal health, data analysis, and human behavior. Design and carry out field studies, collecting and analyzing large data sets. Use and evaluate AI tools to support research and training. Create