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opportunity to align with the most relevant academic department in the College of Architecture, Art, and Planning and teach one course per year subject to department needs. The Postdoctoral Associate will be a
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with expertise in the following four areas: (1) working with large-scale digital trace data; (2) building and running natural language processing and machine learning workflows; (3) experimental design
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, or Stata); · Creating and managing very large datasets; · Machine learning skills. Basic Qualifications A Ph.D. in any business discipline, organizational behavior, economics, statistics, environmental
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
for extension based on mutual interest. We are looking for individuals with a strong theoretical and practical background in large language models, machine learning, and natural language processing, combined with
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will (micro-)benchmark Java-based applications using JMH. You will collect performance measurements from real projects, statistically analyse them, and conduct experiments with modern machine learning
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researchers working on hyperspectral imaging, radiative transfer modelling, machine learning, agronomy, and plant genetics. You will also work with HYDRA-EO partners in Netherlands, Spain and Italy
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about the Shih Lab: Learn more about the innovative work led by Dr. William Shih here: https://www.shih.hms.harvard.edu/ . What you’ll do: Develop DNA-based sensors that seed crisscross assembly of single
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-Sigler Institute for Integrative Genomics and the Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine learning
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employee with a disability. Connections working at University of Rhode Island More Jobs from This Employer https://main.hercjobs.org/jobs/21855054/postdoctoral-fellow-interdisciplinary-cyber-security Return
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Northwestern, TTIC, and UIC. Postdoctoral researchers will conduct research on key aspects of the foundations of data science. This field includes relevant areas of Theoretical Computer Science, Machine Learning