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to apply. We seek candidates with expertise in some or all the following areas: density functional theory, deep learning, high-throughput simulations, molecular dynamics, and materials chemistry. Strong
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new MRI techniques for motion-robust imaging, real-time image processing, and/or deep learning. The work includes MRI pulse sequence design for various MRI techniques and technologies, algorithm and
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NASA. The researcher will utilize multi-decadal satellite imagery and deep learning techniques to analyze temporal trends in urban structure and their impacts on microclimate, focusing on extreme heat
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learning, small data learning · Active learning, Bayesian deep learning, uncertainty quantification · Graph neural networks This position involves active participation in a well-funded
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. - Research Areas: Positions are focused around Deep Learning and Inverse Problem Regularization. Successful candidates will engage in diverse projects ranging from provincial to national levels, in
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learning, deep learning, and large language models (LLMs), for the analysis of high-throughput multi-omics datasets (especially single-cell and spatial omics) and large textual corpora (e.g., scientific
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simulations of PDEs, deep learning, neural networks. Our research interest: Our focus is on theoretical and computational biological physics, ranging from the study of molecules to cells. We strive to leverage
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journal publications dependent on your background discipline(s) and should hold sufficient theoretical knowledge of deep learning-based methodologies as well as working with real-world data. Informal
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faculty member in the Center for Bioinformatics and Quantitative Biology (CBQB) at UIC. The successful candidate will conduct computational research at the intersection of AI/deep learning, bioinformatics
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genomics, virtual cell models Graph-based neural networks, optimal transport Biomedical imaging, deep learning, virtual reality, AI-driven image analysis Agentic systems, large language models Generative AI