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of Direct Ink Writing (DIW) and Laser Powder Bed Fusion (LPBF) techniques for producing high-performance ceramic coal-ash-derived-zeolite (CADZ) filters for strategic adsorption. This project will focus
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and research in several areas. These include, but are not limited to: Adversarial location and network interdiction models Adversarial machine learning attacks and defense (e.g., against Bayesian
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-on experience in infectious disease modeling and vaccinology in an applied government setting while learning and practicing Bayesian methods for nowcasting, forecasting, and Rt estimation. You will also develop
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applying customized Bayesian statistical models for wildlife management and monitoring data. Learning how spatial and ecological modeling approaches are used to study wildlife disease spread and management
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: Experience with surrogacy analyses using regression model and/or meta-analytic model including Bayesian methods and knowledge of continuous glucose monitoring data (or any digitally derived endpoint data
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Implementing Bayesian networks and uncertainty quantification techniques to account for sensor noise and model confidence limits Designing, training, and fine-tuning computer vision models to extract clinically
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statistical modeling (ideally Bayesian statistics) Proficiency in Fortran, C/C++R, Python, and Matlab. Strong computational skills Strong oral and written communication skills Stipend $5,000.00 – $18,000.00
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including breaking dormancy of crop wild relative species, and more efficient long-term seed storage conditions. Data analyses including data handling, filtering, and calculations of genetic diversity
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handling, filtering, and calculations of genetic diversity, relationships, and GWAS/GS. Information is expected to be uploaded into public databases to ensure all data become publicly available. Project
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the genotyping service institution. You can learn to handle and analyze genotypic data including filtering, storage, querying and analyzing to answer questions about genetic identity, relationships, and diversity