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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 4 hours ago
Research Triangle, the United States, and even the world. Position Summary This Postdoctoral Research Associate will conduct advanced research in artificial intelligence, machine learning, computer
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 16 days ago
Research Triangle, the United States, and even the world. Position Summary This Postdoctoral Research Associate will conduct advanced research in artificial intelligence, machine learning, computer
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, Merced is seeking a postdoctoral scholar to work on an NIH-funded project (Project Number: R35GM163973) focused on biomolecular simulations and machine learning applications in biological systems. The
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large language model (LLM) and retrieval-augmented generation (RAG) approaches Systems and mathematical modeling of biological or complex systems Natural language processing and machine learning Data
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electrochemistry and artificial intelligence. Ideal candidates will have experience in machine learning, large language models, AI-agent development and computational workflows, with particular interest in
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collaboration with the pharma industry. Our current research projects include the analysis of: • Plasma, CSF and Brain Proteomic analysis • Biomarker identification through the use of machine learning and AI
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detection, waveform segmentation, feature extraction, hemodynamic modeling, time-series analysis, machine learning, and development of algorithms for real-world clinical data. The fellow will have the
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About the Opportunity SUMMARY The lab of Professor Albert-László Barabási is looking for Postdoctoral Research Associates in the area of network science, nutrition, biological networks, machine
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Experience with multivariate ecological statistics or machine learning and GWA Experience with Field research in agronomy or environmental microbiology Experience with gnotobiotic or controlled
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Experience with multivariate ecological statistics or machine learning and GWA Experience with Field research in agronomy or environmental microbiology Experience with gnotobiotic or controlled