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atmosphere using improved geospatial and activity data for NRCS applications. Update soil inputs of the CONUS EPIC model using the latest soil databases, such as the Gridded National Soil Survey Geographic
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relationships between structure, morphology, performance (reactivity, selectivity, efficiency), and degradation mechanisms under realistic deployment conditions Participation of beam times at international large
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, manage, and analyze diverse datasets, including EHR (EPIC), surveys, interviews, and population-level data. Qualitative & Quantitative Analysis: Conduct interviews or focus groups, perform statistical and
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simulations, design and conduct experiments, and analyze multimodal data streams in a continuous, real-time loop with minimal human intervention (https://www.nature.com/articles/s41524-024-01423-2 , https
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in analysis of large complex data sets, as evidenced by application materials. Strong interpersonal communication skills, as evidenced by application materials. Demonstrated willingness to help mentor
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for projects examining questions in cardiovascular disease using extremely large data sets comprised of routinely-collected clinical data · Developing and maintaining requirements for access to Truveta Data and
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. Some experience with data acquisition in large physics experiments. Familiarity with EPICS - accelerator control software. Experience with Particle-In-Cell codes. Demonstrated ability to communicate
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infections using electronic phenotyping, supervised machine learning, live Epic/FHIR implementations for silent deployment, and multi-site data coordination. https://reporter.nih.gov/search