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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 15 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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Organoid model culturing Mouse model optimization and validation You will report to the Professor Bent Deleuran and Associate Professor Stinne Greisen Your competences You have academic qualifications at PhD
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are gaining significant interest for sustainable seawater desalination. This postdoctoral position is part of a research project aiming to design, optimize, and evaluate electrochemical systems [electrodialysis
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of water intended for agricultural use. The selected candidate will contribute to the development and optimization of desalination processes (membrane-RO), the analysis of treated water quality (especially
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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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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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research engineer with a passion for innovation and strong inter-disciplinary skills; PhD degree in Instrument or Analytical Engineering, Mechanical Engineering, Biomedical Engineering, Systems Engineering
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functionalities remain limited. To address this, the EMMA project will develop sustainable and functional polyolefins by optimizing the flow behavior of post-consumer polyolefins, applying chemical modifications
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the kinetics of enzymatic polymerization processes in biological environments. Expand and tailor enzyme repertoires to optimize functionality and electrode performance. Collaborate within a multidisciplinary and
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monitoring and electric vehicle battery tracking. Integrate environmental and energy sensors with real-time data collection and analysis systems. Deploy prototypes in the field and optimize their performance