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Field
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Apply Now Job Summary The hired postdoctoral researcher will perform independent and directed research to achieve the objectives of the research project within the Department of Computational
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, machine learning, and high-performance computing. Experience in leading the development of new math and algorithms for extracting rotational dynamics from correlation spectroscopy and reconstructing 3D
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Status: Nonexempt Work Schedule: Flexible Summary The intern will receive training on machine learning algorithms, implementing them, and fitting them on the datasets in our cluster computers. Overall
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data and analyzes outcomes. Performs research on current and future HPC, data, and CI technologies, hardware and software. Works on algorithm development, optimization, programming, computer
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. The focus will be on developing algorithms and techniques that optimize beamforming performance to enhance signal acquisition, tracking robustness, and interference mitigation. Benefits Our commitment
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and analyzing large-scale national datasets (e.g., All of Us, CMS), preparing data for NIH- and federally funded studies, and applying advanced statistical and machine learning techniques to informatics
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objectives of the project are to (i) deploy network analysis methods to genomic data (50%), and (ii) develop such algorithms including community detection algorithms (50%). PhD in computer science, engineering
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computer architectures and deliver them as user-friendly software to meet DOE experimental facility needs. What You Will Do: Develop new mathematical theory, algorithms, and code for determining
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for fully automated analysis of nuclear cardiology data using novel algorithms and machine learning techniques, and on the development of integrated motion-corrected analysis of positron emission tomography
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algorithms and topological quantum computation). Appointments of postdoctoral fellowship positions are offered for an initial period of two years, with the possibility of extending for one additional year. The