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Research Fellowship (PRF) for PhD CS Program Location Rio Grande Valley, Texas College College of Engineering and Computer Science Department College of Engineering and Computer Science / Computer Science
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Research Fellowship (PRF) for PhD MSE Program Location Rio Grande Valley, Texas College College of Engineering and Computer Science Department College of Engineering and Computer Science / Mechanical
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application to lineage tracing Algorithms for characterizing structural alterations in bulk and single cell whole-genome data Mutational signature analysis for cancer/brain samples Analysis of repetitive
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Postdoctoral Research Fellow to work on the design, development, and realization of future communications technologies. You will be part of the team and contribute to ongoing developments in theory, algorithms
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 7 hours ago
is important to note that this position is contingent on T32 funding. Education and Experience: PhD in Computer Science, Bioinformatics, Computational Biology, or related discipline. Knowledge of
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Postdoctoral Fellow provides for an internship and continuation of scholarly activity and research after achieving the PhD or other doctoral degree under the direction of a senior faculty member who serves as a
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:00pm Job Summary: The Postdoctoral Fellow provides for an internship and continuation of scholarly activity and research after achieving the PhD or other doctoral degree under the direction of a senior
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to remove PFAS. To accomplish these goals, the candidate will participate in the development of AI/ML algorithms for the prediction of chemical properties, infrared and mass spectra, and ionization cross
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activity and research after achieving the PhD or other doctoral degree under the direction of a senior faculty member who serves as a mentor for the postdoctoral appointee. Additional Department Summary
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Medicine and Bioinformatics. The specific objectives of the project are to (i) deploy network analysis methods to genomic data (50%), and (ii) develop such algorithms including community detection algorithms