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across a range of application areas, including education and healthcare. As these systems are increasingly deployed in high-stakes environments, there is a growing need for machine learning models
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Do you want to combine high-throughput directed evolution with machine-learning analysis of deep sequencing data to engineer better antibodies? The Sormanni Lab in the Department of Chemical
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curious to deliver work that matters, your journey starts here! The Department of Electrical and Computer Engineering (ECE) ranks among the best in the country. Our research programs are at the forefront
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University safety requirements. Machines and Equipment: Operational knowledge of laboratory equipment for mechanical testing of concrete materials Operational knowledge of equipment for 3D Printing of concrete
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to the development of remote sensing algorithms, simulation and modeling capabilities, and artificial intelligence/machine learning (AI/ML) methods in support of the goals of the joint NASA/USGS Landsat mission
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, learning, well-being, social experiences, and decision-making. HARP is developing a longitudinal multimodal research resource to study human-AI interaction and its impacts using student-informed, privacy
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National Energy Technology Laboratory (NETL) | Albany, New York | United States | about 23 hours ago
. Proficiency in machine learning, digital twin technology. Previous peer-reviewed publications. Programming skills. Ability to conduct independent research in a multi-disciplinary team. Point of Contact Jordan
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National Aeronautics and Space Administration (NASA) | Hampton, Virginia | United States | 19 days ago
the computational work. Researchers in the group have experience with crystal plasticity using finite element and fast Fourier transform methods, fatigue indicator parameters, process modeling and machine learning
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 2 hours ago
. Examples include: determination of high-resolution shape models using shape-from-shading or novel machine-learning methods; studies of high-resolution shape models for geophysical and geological studies
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quality and consumer satisfaction. You will also apply statistical and machine-learning tools to explore how physical and chemical fiber parameters relate to dye uptake behavior, dyebath exhaustion, color