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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
researcher with a background in machine learning and/or biomedical image processing. The ACM Lab is developing software to support AI-driven techniques to rapidly diagnose, track, and treat neurodisorders
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enable students to earn associate or bachelor’s degrees through a combination of in-person, online or blended learning. All of our system institutions place strong emphasis on service — helping to build
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 19 days 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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. Proficiency in Python and/or machine learning applications for data analysis. Ability to work independently and manage multiple research activities. Experience contributing to academic publications and
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Documented expertise in developing and training machine learning models (ideally with a focus on LLM), high-performance computing, data management, and software architecture Strong Python programming skills
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, reinforcement learning, theoretical statistics, or related fields. Applicants should have a solid background in probability and statistics/machine learning. The postdoctoral fellow will be mentored by Alexander
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of Applied/Computational Mathematics. Research topics of interest include numerical methods for scientific machine learning and AI, and their applications to various science and engineering disciplines
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methods, integrating qualitative approaches (e.g., interviews, walk-alongs, focus groups) with quantitative techniques (e.g., computer vision, physiological sensing, environmental monitoring, crowd
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industrial partner, you will design and implement innovative architectures for real-time detection and control of laser processes. This interdisciplinary role combines artificial intelligence and machine
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work will involve sophisticated bioinformatic analyses, including the application of machine learning techniques, to predict taxonomic, antibiotic resistance profiles and phenotypes from 'omic data. Your