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Posting Summary Logo Posting Number RTF00226PO26 USC Market Title Post Doctoral Fellow Link to USC Market Title https://uscjobs.sc.edu/titles/156387 Business Title (Internal Title) Post Doctoral
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computational models and machine learning methods, as well as experience in repertoire data analysis. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR8023-CLAMAR-001/Default.aspx Work
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top-tier venues and will have dedicated time for advancing their own research. The project is in collaboration with CCL (The Center for Connected Learning and Computer-based Modeling, PI Uri Wilensky
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this, the postdoctoral researcher will combine machine learning, molecular dynamics simulations and high performance computing (Isambard AI). Applicants must have a PhD in an appropriate area of computational chemistry or
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Department's Website: EECS Department Website: https://engineering.uark.edu/electrical-engineering-computer-science/ Artificial Intelligence and Computer Vision Laboratory Website: https://uark-aicv.github.io
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checks with advanced machine learning architectures, specifically Long Short-Term Memory (LSTM) networks and Variational Autoencoders (VAEs). The researcher will use historical QC archives dating back
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characterization (PXRD and Rietveld refinement, SEM, XPS, etc) Experience with machine learning techniques, particularly machine-learned interatomic potentials, in the context of chemical research. Programming
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considered. General interest in responsible AI, coursework, use of machine-learning tools, unpublished projects, or publications only in unrelated venues do not satisfy this requirement. For collaborative
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intelligence. Our research spans computer vision, machine learning, and natural language processing, focusing on multimodal learning, data fusion, spatial-temporal modeling, and vision–language models. We study
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of engagement. Read more at: Department of Computing Science Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven