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/10.1016/j.xcrp.2022.101112 and https://doi.org/10.1080/08940886.2022.2114716 key words synchrotron radiation; X-ray Absorption Spectroscopy, machine learning, artificial analysis, autonomous experimentation
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to eligible team members. Learn more at https://hr.duke.edu/benefits/ Minimum Qualifications Education See job description for education requirements. Experience See job description for requirements. Degrees
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for AI and Machine Learning included as well as industrial statistics), which will complement our current research portfolio (see https://stat.kaust.edu.sa) and have a research profile that can potentially
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the interplay between mutations, energetics, and evolutionary constraints, including epistatic effects. · Developing or applying machine learning approaches to predict or redesign frustration patterns in proteins
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responsibility of developing predictive tools based on machine learning for the analysis and interpretation of Raman vibrational spectra applied to battery materials. The successful candidate will design and
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integration analytics, machine learning, and/or AI. In addition to carrying out research, the successful candidate will be expected to apply for fellowship funding, contribute to the writing of grants and
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Sign In Create Profile Postdoctoral Research Fellow Springfield, IL, United States | 1004897 Apply Now Share Save Job Posted on: 3/18/2026 Back to Search Untitled Document Postdoctoral Research
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in the 2025 QS World University Rankings by Subjects. For more details, please view: https://www.ntu.edu.sg/eee We are looking for a Postdoctoral Fellow to advance cutting-edge research in the security
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brings complementary and/or additionally new expertise including AI/Machine Learning-based methodologies that can be developed for virtual ligand screening, reverse virtual screening (target fishing) and
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inequalities and Sobolev-type spaces (with Hytönen and/or Korte), 3. Conformal deformations of metric measure spaces and/or general regularity and convergence for graph-based machine learning using stochastic