910 machine-learning "https:" "https:" "https:" "https:" research jobs in United States
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standard tools and computer programs to review data. Assist with data cleaning measures to ensure accuracy of data and preparation of tables. Lead basic activities such as data collection and data entry. May
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Website: https://engineering.uark.edu/ Summary of Job Duties: The Postdoctoral Fellow - Biomedical Engineering will continue investigation of cancer nerve crosstalk in both breast cancer and pancreatic
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modeling, machine learning methods, and applications involving text and other non-traditional data sources. The fellow will contribute to and extend research in these areas, engaging in projects that develop
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will continue to build from our learnings. https://pubs.rsc.org/en/content/articlelanding/2025/gc/d5gc01813g https://pubs.rsc.org/en/content/articlehtml/2018/gc/c7gc03747c https://pubs.rsc.org/en/content
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on applying computer vision, machine learning, and sensor fusion to automatically detect, classify, and localize defects, improving the scalability and reliability of building inspection. Research on 3D
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plans, and paid time off. To access this tool and learn more about the total value of your benefits, please click on the following link: https://resources.uta.edu/hr/services/records/compensation
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a research team. Specific Duties & Responsibilities Run routine and ad hoc reports. Use standard tools and computer programs to review data. Assist with data cleaning measures to ensure accuracy
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 1 month ago
Posting Description PREDOCTORAL RESEARCHER, Economics, to support work at all stages of the research process on projects in economics and applied machine learning / artificial intelligence
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for all UNLV postdocs; and provide professional development programs and networking events for postdocs. UNLV currently employs postdoctoral scholars across a wide range of disciplines. Learn more about
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at the intersection of educational data science, AI in education, and the learning sciences, with additional advisory support from faculty and researchers across learning sciences, computer science, machine learning