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clinical scheduling platforms, with a focus on QGenda and Lightning Bolt. This role is responsible for system configuration, optimization, data integrity, reporting, and end user support to ensure accurate
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 9 hours ago
for numerous retail, restaurant and performing arts discounts, savings on local child care centers and special rates on select campus events. UNC-Chapel Hill offers full-time employees a comprehensive benefits
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 9 hours ago
choose from a wide range of professional training opportunities for career growth, skill development and lifelong learning and enjoy exclusive perks for numerous retail, restaurant and performing arts
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deployment enabling validation and demonstration of real-world applications. For more details, please view https://www.ntu.edu.sg/erian We are looking for a Research Associate to conduct numerical modelling
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, including total compensation, please visit: https://ucnet.universityofcalifornia.edu/compensation-and-benefits/index.html Department Description UCSF School of Dentistry MISSION: Advancing health through
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and numerical methods for modeling and optimization: MatLab, Python, etc. Office tools: Access and VBA programming. Free software tools. Specific Requirements Knowledge: Kinetics and thermodynamics
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skills to assess situations quickly and flexibility in response to changing conditions. Skills in oral and written communication, data analysis and numerical computation to prepare correspondence, reports
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Infrastructure? No Offer Description Area of research: PHD Thesis Job description: Your Job: Energy systems engineering heavily relies on efficient numerical algorithms. In this HDS-LEE project, we will use
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, components, overall system performance) Numerical methods and simulation tools (e.g., Python/Matlab, CFD modelling, optimization) Beyond technical skills, we value people who contribute to a healthy and
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and ML driven screening and optimization workflow to improve the generality of modern synthetic methods. Our first objective is to identify structural patterns and scaffolds that are accessible by