Post-Doctoral Associate – Prof. Suo Yang Lab, University of Minnesota, USA

Summary

The Department of Mechanical Engineering at the University of Minnesota, Twin Cities is seeking a highly qualified Post-Doctoral Associate to join Prof. Suo Yang’s research group. This is a one-year, full-time position (with potential extension for a second year depending on performance, funding, and University requirements). The primary focus of this role is developing advanced high-fidelity Computational Fluid Dynamics (CFD) codes, modules, and tools for novel electrochemical processes, reacting flows, and multiphase physics.

Post-Doctoral Associate – Prof. Suo Yang Lab, University of Minnesota, USA

Designation

• Title: Post-Doctoral Associate
• Job Code: 9546
• Employee Class: Academic Professional & Admin (Acad Prof and Admin)

Job Overview & Key Information

Research Area

• High-Fidelity Computational Fluid Dynamics (CFD) & Solver Development
• Multiphase Flows & Electrochemical Process Modeling
• Reacting Flows & Stiff Chemistry/Transport Source Terms (Combustion, Plasma)
• High-Performance Parallel Computing (MPI) & GPU Acceleration
• Conjugate Heat Transfer (CHT) & Reduced-Order Modeling (ROM / ML / AI)

Location

University of Minnesota – Twin Cities Campus, Minneapolis/St. Paul, Minnesota, USA.

Eligibility / Qualification

Required Qualifications

• Education: Ph.D. in Mechanical Engineering, Aerospace Engineering, Chemical Engineering, Applied Mathematics, Computational Science & Engineering, or a closely related discipline with a strong emphasis on high-fidelity CFD.
• Technical Experience:
  • Advanced CFD solver development, algorithm improvement, and numerical methods for highly coupled, stiff systems of partial differential equations (PDEs).
  • Demonstrated expertise in multiphase flows and stiff chemistry/transport source terms in reacting flows.
  • Strong proficiency in C++ / Java / Fortran 90, Python / MATLAB, and MPI-based parallel computing.
• Publications: Strong publication record as first author in peer-reviewed journals.

Preferred Qualifications

• Experience with 3D conjugate heat transfer (CHT) or fluidic manifold optimization.
• Experience with machine learning/AI frameworks (PyTorch or TensorFlow), reduced-order modeling (ROM), or data assimilation (DA).
• Experience with GPU programming (CUDA and/or OpenACC).

Job Description & Responsibilities

• Theoretical & Numerical Research (55%): Perform high-level theoretical and numerical research; develop CFD codes/modules/tools for new electrochemical processes; collaborate with interdisciplinary University and partner teams and industrial sponsors.
• Publications & Proposals (20%): Author/co-author research publications for peer-reviewed journals, prepare progress reports for funding agencies, present research at academic conferences, and assist with grant proposal preparation.
• Student Mentorship (10%): Serve as a research leader by mentoring Ph.D., Master’s (MSME), and undergraduate students in research planning, technical execution, data analysis, and manuscript preparation.
• Laboratory Organization & Management (10%): Co-manage lab operations, ensure safety protocols, manage data recording and automated data back-ups.
• Other Duties (5%): Support department needs, which may include opportunities to assist with or teach undergraduate/graduate courses.

How to Apply

1. Visit the University of Minnesota Careers Portal.
2. Search for Job ID: 375210.
3. Click the “Apply for Job” button.
4. Complete the online application and attach your Cover Letter and Resume / CV.
5. Additional supporting materials can be uploaded post-application via the “My Cover Letters and Attachments” section under “My Job Applications”.

For disability accommodation during the application process, contact employ@umn.edu or call (612) 624-8647.

Last Date to Apply

Open Until Filled

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