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protocols developed by other research staff or principal investigator of the research project. • Utilize EPIC for screening of NICU census to determine subject eligibility for multiple studies. • Recruit
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assimilation and machine-learning techniques, (b) process understanding of the neighborhood risk of heat waves and fires associated with the change of weather pattern, and (c) novel algorithm development
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validate artificial intelligence (AI) algorithms for analyzing OCT imaging in diabetic macular edema (DME). Data processing and image annotation to support development of AI models trained on OCT scans from
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navigation, and follow-up algorithms. Successful candidates will be required to self-disclose any misconduct history or pending research misconduct investigation including but not limited to sexual misconduct
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Support: Advanced EPIC EMR system complemented by AI tools like Nabla AI for clinic note creation and Evidently AI for medical record summarization. Strong IT and physician-specific support for seamless
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training in MR imaging/spectroscopy or hardware development. Prior success with grant applications. Knowledge of pulse programming environments such as GE EPIC or Siemens IDEA. Prior experience with ultra
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and resolve gaps/disparities in whole-person care. Partake in biopsychosocial distress screening, interdisciplinary communication, collaborative care navigation, and follow-up algorithms. Perform
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required. Required Qualifications: Expertise in one or more of the following areas to solve problems in computational epidemiology as they relate to HAIs: AI, algorithms, discrete optimization, data mining