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/PyTorch for deep learning), possibly theory development, simulation studies, real data analysis, and writing manuscripts. Duration: This appointment is for 1 year, may be extended for a second and/or third
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modeling. 80% research - The project focuses on developing theoretical models using optimization and information theory to improve understanding of plant hydraulic regulation at the leaf, plant, and
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software development (mostly in R, or in Python/TensorFlow/Keras/PyTorch for deep learning), possibly theory development, simulation studies, real data analysis, and writing manuscripts. Starting Date
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of Civil, Environmental, and Geo- Engineering. The person would take the lead on a project co-supervised by Profs. Behrens and Arnold to evaluate microbial degradation of fluorinated pesticides and
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and their application in animal models. There will be opportunities to lead a team of students, contribute to grant writing, engage in professional development, and disseminate results at conferences
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to lead a project related to the transport of bacteria in porous media and multiphase flow. A PhD degree in engineering or earth science is needed. 75% - Conduct laboratory experiments related
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will be given the opportunity to take the lead in writing manuscripts related to this project. On a day-to-day basis, the PA will be responsible for tasks such as analyzing data, generating documentation
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sets. Lead and/or assist with the preparation of research articles, reports, and grants. Disseminate research findings/ Qualifications *All required qualifications must be documented on application
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candidate to fill one Post-Doctoral Associate position. Work in the DDLL includes a number of projects, from a large-scale efficacy trial of educational technology focusing on literacy to secondary analysis
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Regular Job Code 9546 Employee Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job Job Duties: Lead development of core reconstruction and simulation software for the LDMX