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position is available in the group of Prof. Alexey Nesvizhskii at the University of Michigan Medical School. The position will focus on developing computational algorithms and tools for the analysis of mass
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guidance, navigation, and control (GNC) systems. The successful candidate will develop and validate Bayesian and non-Gaussian estimation algorithms, data assimilation methods, and tracking frameworks
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developing cutting edge analytic tools for studying the genome transformation and genomic activities. 70% - The candidate will be mainly focusing on developing machine learning methods and/or AI algorithms
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about diversity at the U: http://diversity.umn.edu Employment Requirements Any offer of employment is contingent upon the successful completion of a background check. Our presumption is that prospective
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models (e.g., YOLO, U-Net, EfficientNet, ResNet, FPN, Fast R-CNN) Computer vision techniques and algorithms Python and relevant libraries (e.g., PyQt, OpenCV, NumPy, scikit-learn), particularly
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, investigation and dissemination of large data sets. Works with research team to develop new algorithms to support studies. Participates in developing hypotheses to be tested and ways of testing it, and conducts
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.]; data management and analysis solutions that assist in storage, investigation and dissemination of large data sets. Works with research team to develop new algorithms to support studies. Assists with
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diversity at the U: http://diversity.umn.edu Employment Requirements Any offer of employment is contingent upon the successful completion of a background check. Our presumption is that prospective employees
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Role You will develop and apply mathematical models and computational algorithms to analyze the structure and evolution of scientific literature. An ideal candidate would bring deep mathematical maturity
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origin, gender, age, marital status, disability, public assistance status, veteran status, sexual orientation, gender identity, or gender expression. To learn more about diversity at the U: http