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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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) to join a dynamic, interdisciplinary research team. Our team performs health economics research to better understand and develop policies to lower health care spending and improve healthcare delivery and
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generalized parton distributions (GPDs). A key component of the PhD will also involve the development of novel algorithms designed to overcome current computational and theoretical challenges in hadron
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algorithms Perform data analysis, test and debug software Develop, implement and execute plans and tests Design and apply basic data sources and security practices Employ source code control techniques Assist
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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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development. The developed algorithms will be compared to the current state-of-the-art in method development using samples provided by some of Flanders’ most demanding industrial chromatography labs. To cover a