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research under PI mentorship. Design, execute, and analyze translational studies focused on hereditary hearing loss and LOXHD1 dysfunction. Develop and characterize preclinical models, including mouse models
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on performance and availability of funding. We are seeking a highly motivated and qualified individual with a Ph.D. in Mechanical Engineering, Materials Science, Chemical Engineering, or a closely related
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: Computational, Quantitative, and Predictive Modeling of Root Systems. This position emphasizes integration of phenomics and other -omics data into predictive frameworks. Research areas may include: Structural
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how genetic and environmental factors interactions shape mucosal immunity and metabolism. Our approach includes state-of-the-art multi-omics, novel organoid culture, genetically engineered murine models
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The Postdoctoral Appointee will be part of an R&D group developing multiphysics modeling tools with applications to nuclear fuel recycling, critical materials recovery and purification, and nuclear
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on simulating nanoalloy structures to create a database for materials characterization. The main tasks include running molecular dynamics and Monte Carlo simulations to model nanoalloys under various
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Society. The laboratory uses state-of-the-art technologies and tissue-specific mutant mouse models to investigate the underlying triggers of cancer-induced neuromuscular dysfunction and musculoskeletal
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
, fabrication, and evaluation of loaded MAPs with clinically relevant dosing. The project will involve integration of materials science, drug delivery, and advanced manufacturing to optimize device architecture
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Job Summary Are you passionate about applying cutting-edge GIS Mapping and Water Quality modeling techniques to address critical environmental challenges? Join us in an exciting initiative aimed
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disciplines. Familiarity with contemporary AI systems (e.g., machine learning, generative models) at a conceptual or applied level. Experience with qualitative or mixed research methods (e.g., ethnography