We are seeking one or two highly motivated and dedicated Ph.D. researcher 
assistants to join our interdisciplinary team. We have several exciting projects 
focusing on data assimilation in fluid mechanics, state estimation, and particle 
forcing reconstruction using turbulence modeling and machine-learning-based 
generative models.

Web Page: https://qiwang.sdsu.edu

Application Process: 
• Visit https://www.engineering.sdsu.edu/admissions/joint-doctoral to see the 
update-to-date detailed requirements.
• Applications for Fall 2024 will be accepted from October 1 to December 15, 
2023
• For inquiries and application submissions, please contact dgeiger@sdsu.edu

Qualifications
• Master's degree in a relevant field, e.g. Fluid Mechanics, Computational 
Science, Applied Mathematics, or a related discipline. Exceptional candidates 
with a bachelor’s degree will also be considered.
• The Graduate Record Examination (GRE) is required with a minimum score, please 
check on https://www.engineering.sdsu.edu/admissions/joint-doctoral
• Strong background in linear algebra, calculus, numerical methods, and 
computational fluid dynamics (CFD).
• Programming languages such as Fortran, Python, MATLAB, or Julia.
• Familiarity with mathematical optimization and its application to complex 
systems.
• Excellent problem-solving skills and ability to work independently and as part 
of a collaborative team.
• Effective communication skills for presentations and scientific discussions.
• Previous experience in inverse problems or nonlinear dynamics is a big plus.