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Field
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data into the software database. Aid in the development of processes, applications, and reports to enhance the efficiency of delivering and integrating Performance Science data into the database
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will apply state-of-the-art machine learning algorithms and custom disease-relevant genomic datasets (e.g., coronary artery single-nucleus chromatin accessibility and RNA sequencing) to develop targeted
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sources to a concrete use case and develop code to test the efficacy and efficiency of algorithms against real-world data. The Front-End Developer will build upon wireframes and concepts created by a UX
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complex process often requiring multiple calls to the patient, referring physician, previous facilities/providers to request records and record review with the clinical team. Independently determine
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are critical especially around congested or critical infrastructures. This research aims to develop decision making and planning algorithms that can mitigate the risks challenging environments of AAM
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at FIU to uplift and accelerate learner success in a global city by focusing in the areas of environment, health, innovation, and justice. Today, FIU has two campuses and multiple centers. FIU serves a
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management systems in complex organizations with multiple stakeholders, authors, and editors. Proven experience in marketing, with a focus on strategic marketing leadership and management within the digital
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climate events in the Western US. CW3E is developing and implementing weather and climate observations, numerical models, machine learning algorithms, and decision support tools focused on atmospheric and
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(PNT) and geolocation systems definition, design and development. The PNT and geolocation domain covers the end-to-end (E2E) engineering of PNT and geolocation systems at system, space, ground and user
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 19 days ago
of the most diverse health databases in history. Nutrition for Precision Health, powered by the All of Us Research Program is a new initiative to develop algorithms that predict individual responses to food and