157 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" uni jobs at Zintellect
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candidates who would like to learn and gain experience in how to plan and perform large animal research and/or burn research in a military medical environment. What will I be doing? As an ORISE participant
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measurements, airborne measurements from field campaigns (e.g., NASA CAMP2EX, ARCSIX) or surface observations. Research involving machine learning techniques will be strongly encouraged. Field of Science: Earth
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• Unmanned Aerial System development, testing, and research • Biomechanics research in musculoskeletal and gastrointestinal systems • Machine learning • Mechatronics and robotic systems • Wind Tunnel
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accurate image labeling and annotation to support supervised machine learning applications. Prepare and gain experience through field experiments, including protocol development, equipment setup, and data
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high school seniors, who are pursuing undergraduate studies in STEM, with an opportunity to explore the world of agricultural science through hands-on learning experiences. Participants will have the
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, machine learning, computer vision, and use of digital data collection strategies is preferred. Ability to communicate about strategies and tools implemented effectively to non-expert audiences. Ability
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in injured war fighter and patients on Extracorporeal Membrane Oxygenation (ECMO). This opportunity provides you, as the faculty participant, the opportunity to learn new scientific applications
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expanded to other microbiome related diseases in the near future. LBP projects focus on the development of assays for assessment and characterization of multi-strain products. Learning Objectives: You will
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research in several areas. These include, but are not limited to: Exploring machine learning techniques to analyze current systems and assess opportunities for improvement Gaining experience with virtual
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learn how phenotypic datasets are integrated with genomic data for association analyses, genomic selection, and AI-driven methods, including machine learning and deep learning, to enhance germplasm