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cotton, corn, peanut, wheat, and soybean—by integrating crop simulation models (e.g., DSSAT, APSIM) with remote sensing (multispectral/hyperspectral, and advanced data science methods. The successful
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changing world: A multiple case study” research initiative, which has been recommended for funding by Mississippi Alabama Sea Grant. This mixed-methods project will constructively evaluate the long-term
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in the following areas: Deep Learning, Scientific Machine Learning, Stochastjc Gradiant Descent Method, and Numerical PDE’s - Advised by Dr. Yanzhao Cao Probabilistic Graph Theory (Network Traversal
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Applicants must have earned a PhD or equivalent degree in Mathematics, Statistics, or a closely related field by the time appointment begins. The candidates selected for this position must be able to meet
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academic references · Code sample or link to your GitHub/GitLab profile · Two writing sample of your previous research work Minimum Qualifications Applicants should have completed their PhD at the time
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, workshops, and outreach events. Candidates should submit a detailed cv, transcripts, and three professional references. Candidates must have a PhD in Mathematics, Statistics, or related field at the time
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research grants and projects in the College. We are seeking applications from individuals with either: (1) a PhD in any area of the biomedical sciences or (2) a DVM or its equivalent at the time employment
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linked diseases at the molecular, cellular, and whole animal levels. The successful candidate will work in close collaboration with the laboratory of Elizabeth Lipke, PhD in the Department of Chemical
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the Southeastern U.S. is likewise desirable. Familiarity with advanced methods for chemical and biological analyses of algae culturing and biomass is additionally desirable. Special Instructions to Applicants