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, together with research experience in at least one class of modern generative models, are particularly encouraged to apply. In addition to conducting research, the successful candidate will teach two courses
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Chekouo and his collaborators within and outside the University of Minnesota. The research will focus on the development of Bayesian statistical/machine learning methods for the data integration analysis
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Magnetics; Micro and Nano Structures; Sustainable Energy Systems, Power Electronics and Drives; Systems and Controls. To learn more about the Department of Electrical and Computer Engineering at
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transfer (CHT) or fluidic manifold optimization Experience with machine learning/AI (PyTorch or TensorFlow), reduced-order modeling (ROM), or data assimilation (DA) Experience with GPU programming (CUDA and
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, Cancer Biology, or a related field. Preferred Qualifications: • Strong background in cancer biology and immunology, with expertise in cellular immunotherapy techniques (e.g., CAR-T cell therapy, TCR
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, ventriculomegaly). Experience in machine learning statistical methods. Experience in the acquisition of infant neuroimaging data. Prior experience working with infants and children in a research setting. Enthusiasm
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models motivated by biological and therapeutic applications are particularly encouraged to apply. Expertise in statistical or machine-learning methods is also welcome, as connection with experimental and
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independently operate 3T and 7T scanner consoles Learn the CNS Lab developmental neuroimaging standard operating procedures o Follow and assist with development of research protocols to ensure adherence to and