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Field
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heterogeneity at the molecular level, primary cells and tissues obtained from osteoarthritic patients will be endotyped using advanced mass spectrometry-based proteomics. Endotype specific primary cell cultures
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Materials: Please submit the required application materials to Dr. Mei-Sze Chua at mchua@stanford.edu (link sends e-mail) Does this position pay above the required minimum?: No. The expected base pay for
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-informed neural networks (PINNs) for integrating mechanistic constraints into ML frameworks, and creating LLM-based agents to assist with mechanistic model construction and knowledge curation. Track B
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“Equilibrium Learning, Uncertainty, and Dynamics.” About the Project Market interaction is increasingly automated by artificial learning agents. Examples include pricing agents in electronic retail or bidding
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databases and retrieval-augmented generation (RAG) and integrate agentic AI systems to meet the demands of large-scale fine-tuning and inference. The postdoc will also work on design and implement agentic-AI
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modeling, or agent-based modeling, who are eager to incorporate socio-political dynamics into their models; or2.Computational social scientists with experience in empirical research and/or theoretical
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the postdoctoral researcher will be a part: Carole Adam, Senior Lecturer at the UGA. The objective of the project for UGA is to design and implement an agent-based simulator to evaluate coordinated response
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supervision of PI Calina Copos and will engage in collaborative work with cell and developmental biologists. Expertise in agent-based models, continuum PDE descriptions, dynamical systems, and/or ML-based
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osteoarthritic patients will be endotyped using advanced mass spectrometry-based proteomics. Endotype specific primary cell cultures will be then established using animal free culture media and will be genetically
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. The preferred candidate will have a strong academic or industrial background in machine learning, trustworthy machine learning and AI, agentic AI, adversarial machine learning, graph-based learning, multi-domain