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partners, along with the databases we create. The geospatial smoke tradeoffs dataset can then be used in project planning. Learning Objectives: The fellow will develop professionally while engaging in
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use of molecular assays such as real-time PCR and next-generation sequencing to study the prevalence of infectious diseases in the target study populations. Learning about sample testing under a
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transmission and spread. Learning Objectives: Under the guidance of a mentor, the participant will learn to or increase their ability to: collect and extract samples for sequencing. construct libraries and
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condition leading to medical discharge following combat related trauma in our military. Learning opportunities include, but are not limited to: exposure to various aspects of pre-clinical research by
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development pertaining to chemical and biological detection. You will gain experience with algorithms, data analysis, Deep Learning, Python, pytorch and /or tensorflow, NLP, genetic algorithm, computer vision
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improve federal transit operations and oversight. Projects may include: Performing exploratory data analysis across diverse FTA datasets. Building and evaluating statistical and machine learning models
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findings into manuscripts for peer-reviewed journals. Learning Objectives: Throughout the course of this research project, the participant will have the opportunity to explore the latest trends and research
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Analyzing results and simulating environments of interest Quantum Information and Sensing Nuclear Science and Weapon Effects Artificial Intelligence, Machine Learning, and Cyber Security Materials, Extreme
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results to classical theory. Learning objectives will include accessing NETL's unique experimental equipment and facilities to further the fundamental understanding of fracture propagation as a function of
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, data processing and report generation will be the activities performed to accomplish the project objectives. Learning objectives will include performing data collection with NETL's unique suite of non