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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 7 hours ago
experiments, optimize protocols, document procedures and results, collate and analyze data, and communicate results and conclusions in written and oral formats. They will have the opportunity to train and
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chemical–biological pathway. The advertised positions will support these efforts through research on advanced carbon capture methods, process modelling and optimization, and biological CO₂ valorization in
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for: design and optimize bioprocesses for cultivated meat production, including media formulation, cell growth, differentiation, and harvesting techniques; conduct and optimize the production of porcine and
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to translate this knowledge into innovative, optimized vaccine candidates (PMIDs: 35015104, 34990590, 33323394, 30439392; patent: WO2024003343A1). About the Project: You will contribute to a project
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studies: Trauma Intervention to Optimize PrEP Among Women Who Inject Drugs (TIARAS) is a randomized controlled trial is to test the effectiveness of a trauma intervention designed to reduce HIV acquisition
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. This position offers an exciting opportunity to work at the intersection of HPC and AI, addressing critical communication bottlenecks and optimizing network interconnects for large-scale distributed systems
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hydraulic modeling. 80% research - The project focuses on developing theoretical models using optimization to improve understanding of plant stomatal regulation at the leaf, plant, and ecosystem scales. 20
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mark on the national, continental, and global stages. Job Description: We are seeking a postdoctoral researcher specialized in the modeling and optimization of waste management systems. The successful
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help! We have several fully-funded open PhD and Post-Doc positions (m/f/d, E13 TV-L) in our group - which just moved from the Max Planck Institute in Erlangen to the University of Tübingen, one
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-optimal production outcomes. Deviations from normal behavior have diverse causes, ranging from misplacement, heterogeneity in material, to fatigue. Locating such issues in the production line can be