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murine and patient derived cell lines for in vitro modeling to examine tumor cell lipid metabolism. Prepare figures, manuscripts, abstracts, and grant submission materials for publication and/or
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strongly relies on the interaction between wind and dune shape. Recent improvements in airflow modelling and coastal dune modelling are promising. However, getting accurate wind field predictions remains
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National Aeronautics and Space Administration (NASA) | Hampton, Virginia | United States | 15 days ago
-sensitive modeling, high-fidelity experimental characterization, and uncertainty quantification capabilities for metallic aerospace materials, with emphasis on additively manufactured (AM) metals
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, electromagnetic modelling, additive manufacturing, materials characterisation and experimental validation. The appointee will work closely with the Chief Investigator (CI), Partner Investigators (PIs), research
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extreme weather forecasting, employing data science models as developed in computer vision and natural language processing (NLP). This project leverages the large-scale high-performance computing (HPC
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to pharmacological intervention. We will combine studies in GPR6 knockout mice with pharmacological approaches in rodent models, including Flinders Sensitive Line (FSL) rats, a model of depression. By linking
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, plasma polymer growth mechanisms, and the physicochemical properties of the resulting coatings, and for transferring the optimized conditions from model surfaces to magnetic nanoparticles. The main
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, etc.) to model materials in high temperature or high stress conditions. Experience working with high pressure systems and pressure control systems. Experience setting up data acquisition systems and
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underlying juvenile dermatomyositis and related pediatric conditions. Through the integration of advanced molecular techniques, patient-derived samples, and functional muscle modeling, you will help develop
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convection. The objective is to develop reduced but realistic models of cumulus life cycles that may be applied toward cumulus parameterization and/or machine-learning algorithms for predicting short-term