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on applying, developing and implementing novel statistical and computational methods for integrative data analysis, causal inference, and machine/deep learning with GWAS/sequencing data and other types of omic
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related field Strong oral and written communication skills Demonstrated motivation, initiative, and attention to detail Deep interest in translational neurotechnology, medical device development, and
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following areas: 1) statistical genetics/genomics/omics, or 2) deep learning/AI. Most importantly, we value candidates who demonstrate both the ability and drive to rapidly learn and implement recent advances
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this position you may also have the opportunity to teach courses offered in our department. These duties would be to prepare and deliver lectures, prepare homework assignments, quizzes and exams, hold office
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of the following backgrounds are particularly encouraged to apply: Machine learning and deep learning, particularly for time-series modeling Structural health monitoring (SHM), including fiber-optic sensor
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in the University of Minnesota. The research will focus on applying, developing and implementing novel statistical methods for causal inference, integrative data analysis or/and machine/deep learning
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a 3-year DOE-sponsored project that started in September 2024. The Postdoctoral Research Associate working on P1 will develop and test deep learning algorithms for model emulation and model parameter