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Field
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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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central area of expertise. The successful candidate shall demonstrate deep knowledge of LCA methodology and tools, and show strong competencies in methodological development and application across various
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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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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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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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learning methods. Develop deep learning architectures (e.g., variational autoencoders, graph neural networks, transformers) for cross-omics data representation and feature extraction. Apply multi-view
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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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to work on a project at the intersection of deep learning and computer security/privacy, under the direction of Dr. Michael Wu. The project seeks to investigate security and privacy problems in deep
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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
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The Role The successful applicant will be responsible for the design, development, and implementation of deep learning and computer vision frameworks across a range of research projects