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Field
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-series data, or other high-dimensional biomedical datasets. Strong foundation in signal processing, statistical analysis, computational modeling, or algorithm development. Ability to process, clean
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but not limited to the following areas of Computer Science: Object-oriented programming, Data Structures and Algorithms, Software Development on Windows/Unix platforms, Web development, Artificial
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Computer Science, Information Systems or related technology field, or an equivalent combination education and experience. Certifications/Licenses Required Knowledge, Skills, and Abilities Highly motivated candidate
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clear updates on program status to Fleet-level personnel at both individual and community meetings Interact and collaborate regularly with the engineering team, principal investigator, sponsors, and other
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project tasks Develop and deliver clear updates on program status to Fleet-level personnel at both individual and community meetings Interact and collaborate regularly with the engineering team, principal
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project tasks Develop and deliver clear updates on program status to Fleet-level personnel at both individual and community meetings Interact and collaborate regularly with the engineering team, principal
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Postdoctoral Associate Required Qualifications: (as evidenced by an attached resume) ● PhD (or foreign equivalent) in Applied Mathematics, Physics, Theoretical/Computational Biology
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learning, edge computing, development of novel AI algorithms for agricultural applications, embodied AI, simulation to reality transfer, and systems engineering incorporating big data and artificial
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 15 days ago
Posting Information Posting Information Department Renaissance Computing Inst-637100 Career Area Research Professionals Posting Open Date 09/08/2026 Application Deadline 09/21/2026 Open Until Filled
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visualizations and interactive tools. Engages in best practices in data analytics and data engineering - including robust validation processes, testing/deployment procedures, algorithms for data mining, version