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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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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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, 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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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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the Division of Student Academic Success, comprised of the Vice Chancellor for Student Academic Success, Office of Retention, Center for Learning and Student Success, Educational Opportunity Fund (EOF), TRIO
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applications in chemical and pharmaceutical manufacturing; data-driven modelling and machine learning applications in process industries; advanced process control (APC); model predictive control (MPC); digital
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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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possible for up to 1 day/week. You will join an interdisciplinary team of researchers spanning imaging science, machine learning, genetics, and population health, working closely with collaborators