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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 23 hours ago
and professional sustainability. We optimize our partnership with the UNC Health System through close collaboration and commitment to service. OUR VISIONOur vision is to be the nation’s leading public
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performance of optimized industrial formulations; Computational simulation of materials and solutions using numerical methods; Preparation of reports and scientific papers for the dissemination of results. V
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to optimize patient outcomes. Responsibilities : The selected candidate will have a central role in the implementation of the "EMULATE" project, which aims to: assess the feasibility of generating evidence
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 23 hours ago
, and create personal and professional sustainability. We optimize our partnership with the UNC Health System through close collaboration and commitment to service. OUR VISION Our vision is to be
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collection. Evaluate protein content, nutritional value, and functional properties of yeast biomass in various fermentation processes. Develop and optimize both liquid fermentation strategies offering high
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Job Description As part of our laboratory's research initiatives, we are conducting advanced research on the computational modeling and optimization of heterogeneous catalysts for various catalytic
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, including publication. Lead the development, optimization, and execution of stem cell-based brain cell differentiation, focusing on hiPSCs-derived neurons and microglia. Design and conduct in vivo experiments
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; You will participate in collaborations in materials optimization, device fabrication, and testing. Required Knowledge, Skills, and Abilities: You earned a Ph.D. in an appropriate discipline (Physics
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including code design, documentation and testing. Familiarity with optimization methods including Machine Learning (ML) techniques. Any experience with computations on GPUs. Working knowledge of Linux command
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control for medical robotics in the context of cardiovascular technologies. The goal is to innovate control systems for optimized interaction of soft cardiovascular pumps and wearable biofeedback systems