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Postdoctoral Researcher in Machine Learning of Isomerization in Porous Molecular Framework Materials
broad range of applications. Computational chemistry and Machine Learning increasingly underlies MFM research to search or screen candidate MFMs prior to synthesis. A major drawback when applying
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approaches. The institute operates at the intersection of natural, and medical sciences and the humanities. Information on the institute can be found at www.globe.ku.dk . The research will be conducted
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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 09-Jul-25 Location: Auburn, Alabama Categories: Academic/Faculty Agricultural Sciences Internal Number: 49851 Job
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: 273379270 Position: Postdoctoral Research Associate Description: The group of Prof. Aditya Sood in the Department of Mechanical and Aerospace Engineering and the Princeton Materials Institute at Princeton
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Research Center, and is closely affiliated with the Jonsson Comprehensive Cancer Center and the Molecular Biology Institute. The G.O. Discovery Lab performs highly innovative and collaborative translational
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, transportation, and more, with a special emphasis on grid resilience assessments and equity analysis. You will have the opportunity to creatively use interdisciplinary methods from computational data science
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engineering, with applications in energy systems and other natural and engineered networks. Additional Information: Hiring Salary: $61,800 Application materials should include: - Cover letter outlining your
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Health Sciences PhD Program), and community engagement activities, we promote patient-centered health care and the delivery of evidence-based health innovations that improve population health and reduce
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previous research experience (computational and experimental) in the broad area of Nonlinear Mechanics. Applicants must have received a Ph.D. in Mechanical Engineering, or any closely-related field
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About the Role This Postdoctoral Research Associate (PDRA) position is part of an exciting EPSRC-funded programme, "Enabling Net Zero and the AI Revolution with Ultra-Low Energy 2D Materials and