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of hydrate distributions and fluid migration in porous media under in situ conditions, and • Machine learning application to gas hydrate system to develop efficient key parameter estimation tools and large
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resolution visualizations of hydrate distributions and fluid migration in porous media under in situ conditions, and • Machine learning application to gas hydrate system to develop efficient key parameter
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and expected carbon remaining. The successful applicant will collaborate closely with research scientists and analysts at the Missoula Fire Sciences Lab on this project. The participant will learn
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in genetically modified maize hybrids. Outcomes will contribute long-term goals to develop tools to detect and monitor resistant insects in field populations. Learning Objectives: Participants will
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Engineering 1: Under the guidance of a mentor, this Lifecycle Engineering program area will teach you how to utilize chemical, biochemical, and systems engineering to develop and design solutions that continue
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is for STEM-focused undergraduates, and recent graduates, with a strong interest in STEM professions. Under the guidance of a mentor, you will learn how to utilize mechanical, electrical, computer, and
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, program rules, and availability of the participant. Appointments will be conducted virtually. $125 per week stipend based on part-time participation each week. Program provides the opportunity to learn from
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and binding mechanisms for the lithium observed in formation and related geologic formations. The learning objectives for this project are: · Conduct research about the lithium isotopes (d7Li
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and Data Science (including machine learning and AI for defense applications) - Systems Engineering and Engineering Management - Industrial Engineering and Production Management - Mathematical Modeling
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machine learning, image recognition, and prediction of damage to tree nuts from insect pests. They will also collaborate with other team members on statistical analysis of data collected as part of