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candidates may include: 1.Energy modelers with expertise in integrated assessment modeling, energy system modeling, or agent-based modeling, who are eager to incorporate socio-political dynamics
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candidates may include: 1.Energy modelers with expertise in integrated assessment modeling, energy system modeling, or agent-based modeling, who are eager to incorporate socio-political dynamics
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novel machine learning models—including Physics-Informed Neural Networks (PINNs), variational autoencoders, and geometric deep learning—to fuse multimodal data from diverse experimental probes like Bragg
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-based models as well as patient-derived xenograft models of liver cancer. This position is suitable for a highly motivated self-starter who excels in a dynamic environment offering varied learning
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principles and theories. 5. Develops advanced analytical models and systems and provides solutions and analyses to support strategic and tactical decisions. 6. Adheres to University and unit-level
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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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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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assessment of lymphatic flow, 2) Advancing methods for contrast-enhanced MRL, 3) Creating ideal contrast agents for MRL, and 4) generating phantom and animal models for MRL optimization and validation
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intensive multi-cellular agent based models (ABMs) of Epstein–Barr Virus (EBV) and HIV-1 infection dynamics in human lymphoid tissue. This postdoctoral associate will collaborate with experimentalists
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the intersection of crop-switching, environmental resilience, and agrifood sustainability. The candidate will develop and apply spatial analysis, remote sensing, and modeling to evaluate the technical, environmental