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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 11 days ago
, statistical genetics, and genetic epidemiology, involving large human genetic studies. This 12-month full-time position is open at the Assistant Professor rank. Minimum Education and Experience Requirements
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 17 hours ago
, statistical genetics, and genetic epidemiology, involving large human genetic studies. This 12-month full-time position is open at the Assistant Professor rank. Minimum Education and Experience Requirements
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. The investigator applies advanced statistical techniques to discover mechanistic pathways driving severe patient deterioration. Continuous collaboration with intensive care physicians ensures the clinical relevance
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with existing population and demographic monitoring data held by the British Trust for Ornithology. Statistical modelling approaches will examine spatiotemporal changes in bird distributions in response
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statistical methods to large-scale medical datasets (EHR, imaging, genomics, clinical trials). Design algorithms and predictive models to advance diagnostics, medical devices, healthcare access, and
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/ *This position is fully paid and visa may be arranged Basic Qualifications • Bachelor’s or master’s degree in economics, mathematics, statistics, computer science, or related fields • Strong quantitative and
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Postdoctoral Benefits page.) CAMPUS SECURITY CRIME STATISTICS Pursuant to the Jeanne Clery Disclosure of Campus Security Policy and Campus Crime Statistics Act and the Pennsylvania Act of 1988, Penn State
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of Campus Security Policy and Campus Crime Statistics Act (Clery Act), each year the University of Arizona releases an Annual Security Report (ASR) for each of the University’s campuses. These reports
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/trait data) Conducting statistical modeling, feature selection, and predictive analytics for forest health, resilience, and biomass estimation Supporting data preprocessing, cleaning, normalization, and
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Saelens team. Research Project In this research project you will develop probabilistic deep-learning models that automatically extract biological and statistical knowledge from in vivo perturbational omics