About the role
Position Summary
The successful candidate will work with Dr. Kunlun Qi < https://kunlun-qi.github.io> on research projects related to kinetic equation and its related multiscale model reduction, numerical method, and data-driven/machine-learning approaches, including:
- Numerical simulation of kinetic equations: fast algorithms with stability/convergence analysis;
- Data-driven and machine learning-assisted methods: data assimilation, uncertainty quantification (UQ), and machine-learning-based moment closure models.
- Multiscale modeling: kinetic limits of many-particle dynamical systems, hydrodynamic limits of kinetic models, and semiclassical limits of quantum systems.
- Theoretical analysis for kinetic PDEs: Well-posedness and asymptotic behavior of the Boltzmann equation and related models
Equal Employment Opportunity Statement
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, citizenship, age, disability or protected veteran status.
Required Degree
Terminal -Ph.D. in Mathematics, Statistics, or a closely related field by the start of the appointment.
Minimum Requirements
Ph.D. in Mathematics, Statistics, or a closely related field by the start of the appointment.
Desired Qualifications
Candidates with strong backgrounds in kinetic equation, numerical analysis, scientific computing, PDE together with research experience in scientific machine learning, are particularly encouraged to apply.
Required Application Materials
Applications will be reviewed immediately and will continue until the position is filled. Applicants should submit:
- A curriculum vitae;
- A research statement describing prior and current research, future research plans, and specific interests related to the project;
- At least two letters of recommendation.
Special Instructions
Prospective candidates are welcome to contact Dr. Kunlun Qi at qikunlun@msu.edu. Please include “Postdoc Applicant – Your name” in the subject line and briefly describe any overlap between your research interests and the topics of the position. Applications and all supporting materials must be submitted electronically through MathJobs.
If you are perspective graduate students who are interested in our research, we are also looking for self-motivated Master/PhD joining our group, please see more details in our graduate program and contact Dr. Kunlun Qi at qikunlun@msu.edu
Review of Applications Begins On
10/14/2026
Website
https://cmse.msu.edu/
Department Statement
Michigan State University (MSU) is one of the top public research universities in the United States, located in the scenic city of East Lansing, Michigan. MSU boasts world-class research capabilities, a diverse and inclusive campus culture, and abundant academic resources. It has a strong academic reputation in applied mathematics, computational science, and mathematical physics—making it an ideal place for academic development and research exploration.
The Department of Computational Mathematics, Science and Engineering (CMSE) was founded in 2015 as an interdisciplinary department jointly administered by the College of Natural Science and the College of Engineering. CMSE centers around computational approaches, encompassing algorithm development, high-performance computing, scientific modeling, and data science. The department has an active research community with strengths in computational biology, bioinformatics, machine learning, optimization, scientific computing, statistical data analysis, and topological data analysis. CMSE offers undergraduate, master’s, and Ph.D. programs in data science, emphasizing both research and teaching to support student growth.
MSU Statement
Michigan State University has been advancing the common good with uncommon will for more than 160 years. One of the top research universities in the world, MSU pushes the boundaries of discovery and forges enduring partnerships to solve the most pressing global challenges while providing life-changing opportunities to a diverse and inclusive academic community through more than 200 programs of study in 17 degree-granting colleges.