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predictive modeling approaches to understand corrosion mechanisms and coolant/fuel chemistry in extreme conditions. The successful candidate will oversee corrosion-focused projects sponsored by industry and/or
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candidate will join Dr. Siddharth Saksena’s research group, which focuses on advancing hydrologic modeling, flood forecasting, and hydroinformatics through the integration of artificial intelligence, physics
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on their research and innovation campus. Required Qualifications - PhD and/or MD in Computational Biology, Bioinformatics, Genomics, Biology, Data Science, Computer science or other related fields. PhD must be
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of causal machine learning and optimal policy learning. • Proficiency in other languages such as Stata, and/or Python modeling languages. • Research experience using Python. • Experience working with large
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, 2022 ( https://www.nature.com/articles/s41593-022-01109-2 ) The successful candidate will work with mice and conduct in vivo neurophysiology with molecular tools, data analysis, and modeling (using
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supervision of Prof. Yingda Cheng on computational methods and modeling for kinetic equations. The research conducted will involve development of numerical methods, development and analysis of reduced order
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jurisdictions utilizing land use-value assessment estimates. Duties include, but are not limited to: development of computational methods, maintenance of current models and data sets, identifying and testing
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CRISPRai and optogenetic control systems and developing predictive metabolic models for the oleaginous yeast Yarrowia lipolytica. This position offers a unique opportunity to conduct cutting-edge research
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microenvironment. The project will employ genetically engineered mouse and human glioma models, along with advanced imaging techniques, single-cell and spatial transcriptomics, and molecular biology approaches
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responsible for preparing and utilizing chemical solutions in in-vitro experiments in a wet lab setting, maintain colonies of mouse models of human disease through husbandry and genotyping. The successful