Computational Materials and Chemistry, Postdoctoral Research Fellow

MTSU Jobs•Murfreesboro, TN

About The Position

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

Requirements

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
A terminal degree in materials science, chemistry, computer science, condensed matter physics, or a closely related interdisciplinary field is required by the appointment date.

Nice To Haves

Applicants familiar with defect calculations, band structure/density of states analysis, phase stability, or transport property calculations and who have published SCI-indexed papers in computational materials science or AI for Materials will receive special consideration.