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distributed energy resources (DERs). Design & develop optimization algorithms/tools to plan the deployment of DERs such as energy storage systems (ESS), photovoltaic generations (PV), electric vehicle charging
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 12 hours ago
initiative to develop algorithms that predict individual responses to food and dietary patterns. The NPH Consortium consists of 12 awardees across the US with whom UNC is partnering to implement data
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. The open positions are attached to three different collaborative projects with related but distinct goals, all making use of our expertise in squeezing-based entangled states of light: ClusterQ (ERC): A
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, notably: The interpretation at different time scales (note, pulse, measure, ...) guided by tempo adaptation strategies The development of a simplified improvisation system using a meta-instrument The
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. Of particular interest is the modeling of transport networks across multiple scales, including their function, development and remodeling. We employ advanced computational and theoretical techniques, such as
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. We have multiple NIH-funded projects to study the influence of FDA-approved GLP-1R agonists on drug seeking and reinstatement in rodents. A newly funded NIH R01 has the goal to determine who may be
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within different research areas including the Global Burden of Diseases (GBD), Injuries, and Risk Factors; Future Health Scenarios; Cost Effectiveness and Efficiency; Resource Tracking; and Impact
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provide insights into comparative physiology across different species. Of particular interest is the modeling of transport networks across multiple scales, including their function, development and
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the development of sound method and analytical approaches. You thrive in a collaborative work environment and can work on multiple projects concurrently while meeting deadlines. You keep current of recent
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, their solution uses mathematical algorithms to identify precise differences in content and data, delivering high-speed performance at scale. The project will explore AI technologies for compare-and-merge