Computational Materials and Chemistry, Postdoctoral Research Fellow 498500 Murfreesboro, Tennessee, Tennessee, United States Engineering Sciences Postdoctoral Research Fellow Job Title Computational Materials and Chemistry, Postdoctoral Research FellowDepartment Chemistry University Expectation MTSU seeks candidates committed to innovative teaching and meaningful service. We also seek to attract culturally and
academically diverse faculty who value working with diverse students. Salary The salary is commensurate with education and experience. Job Summary/Basic Function The Department of Chemistry at Middle Tennessee State University invites applications for a full-time postdoctoral research fellow position in computational materials and chemistry This is a one-year temporary appointment with the possibility of renewal for
an additional year. The start date is as early as August 1, 2026. Dr. Zhen Jiang’s research focuses on computational chemistry and materials theory, with particular interests in reaction mechanisms, ion/electron transport in catalytic and energy materials, and data-driven materials design. The group combines first-principles calculations (DFT), multiscale modeling, high-throughput computation, and machine learning to
study and rationally design novel catalytic and energy materials. The group’s long-term research directions include: Reactivity in bulk materials and interfaces. Reaction mechanism modeling. Machine-learning-assisted materials design Machine-learning-assisted development of kinetic methods. Materials database construction and data mining. Related work has been published in leading international journals, including
Science, Nature Energy, Nature Materials, Journal of the American Chemical Society, Advanced Materials, and ACS Catalysis. The group also maintains long-term collaborations with multiple experimental and theoretical research teams in both the United States and China. Personal Website: https://zhenjiang16.github.io/Homepage/ Google Scholar: https://scholar.google.com/citations?user=252n0esAAAAJ&hl The successful
candidate will have the following Solid background in first-principles calculations or materials modeling (such as VASP, Quantum ESPRESSO, etc.) Good Python programming skills Experience in high-throughput computation, data analysis, or machine learning Demonstrate strong research independence Required Education A terminal degree in materials science, chemistry, computer science, condensed matter physics, or a
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