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. The position will focus on developing computational algorithms and tools for the analysis of mass spectrometry-based proteomics data. Research projects will center on advancing the FragPipe computational
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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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development, and through leadership activities in Michigan, nationally and internationally. Our mission is guided by our Strategic Principles and has three critical components; patient care, education and
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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, 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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Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job A Postdoctoral Research Fellow position is available to work on research related to development of predictive display systems
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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