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Field
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computational analysis, including algorithm development, will be integrated throughout the program. Managing collaborations with other research programs within and outside of the lab will be necessary
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on primary human samples derived from blood or tissues in individuals with characterized infection or tumor histories. Using a combination of bioinformatic and computational approaches, we will integrate
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Position Details Position Information Recruitment/Posting Title Open rank tenure track faculty position in the Department of Library and Information Science, in Information Policy Department SC&I
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research across diverse basic and applied science and engineering domains. Responsibilities will include: ● Design, develop, and deploy ML/DL algorithms for domain science and engineering fields ● Support
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 7 days ago
the possibility of reappointment for an additional year. It will involve developing, implementing, and validating novel algorithms for analyzing SWOT data; writing scientific papers; and presenting research
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 14 hours ago
the possibility of reappointment for an additional year. It will involve developing, implementing, and validating novel algorithms for analyzing SWOT data; writing scientific papers; and presenting research
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Qualifications: (as evidenced by an attached resume) * Ph.D. degree in Data Science, Computer Science, Bioinformatics, Biomedical Engineering, Computational Biology, Neuroscience, or a related field. * 5 years
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Application Deadline 12 Sep 2025 - 23:59 (Europe/Lisbon) Type of Contract Temporary Job Status Full-time Hours Per Week 35 Is the job funded through the EU Research Framework Programme? European Union / Next
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Department School of Computing, Chair Compensation Negotiable General Description/Primary Purpose: The School of Computing is seeking a 9-month, tenure-earning, Assistant Professor of Computing
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to accelerate evaluation of costly simulations Genetic algorithms and other evolutionary techniques to generate a diverse set of high-performing solutions. You will design and implement new optimization