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Middle Tennessee State University

Computational Materials and Chemistry Postdoctoral Research Fellow Middle Tennessee State University in United States

Degree Level

Postdoc

Field of study

Computer Science

Funding

Available

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Country

United States

University

Middle Tennessee State University

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Keywords

Computer Science
Chemistry
Computational Chemistry
Multiscale Modeling
Density Functional Theory
Electron Transport
Matter Theory
Energy Materials
First-principles Calculation
Physics
ML

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About this position

The Department of Chemistry at Middle Tennessee State University invites applications for a full-time postdoctoral research fellow in computational materials and chemistry. The project is centered in Dr. Zhen Jiang’s research group and focuses on computational chemistry and materials theory for catalytic and energy materials.

The fellow will work on problems spanning reaction mechanisms, ion and electron transport, and data-driven materials design. The group combines first-principles calculations, multiscale modeling, high-throughput computation, and machine learning to study and rationally design novel materials. Research directions highlighted in the posting include reactivity in bulk materials and interfaces, reaction mechanism modeling, machine-learning-assisted materials design, machine-learning-assisted development of kinetic methods, and materials database construction and data mining.

The advert also notes that the group has published in leading journals and maintains long-term collaborations with experimental and theoretical research teams in the United States and China, suggesting a broad and collaborative research environment for the successful fellow.

Funding details

Available

What's required

A terminal degree in materials science, chemistry, computer science, condensed matter physics, or a closely related interdisciplinary field is required by the appointment date. Applicants should have a solid background in first-principles calculations or materials modeling such as VASP or Quantum ESPRESSO, good Python programming skills, experience in high-throughput computation, data analysis, or machine learning, and strong research independence. Special consideration is given to candidates familiar with defect calculations, band structure and density of states analysis, phase stability, or transport property calculations, and to applicants with SCI-indexed publications in computational materials science or AI for Materials.

How to apply

Apply through the online application system using the application link. Include a cover letter, curriculum vitae, and research statement with your submission. Contact Zhen Jiang for position-specific questions if needed.

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