Beihang University
4 days ago
Postdoc in Deep Learning, Data Assimilation, and Turbulence at Beihang University Beihang University in China
Degree Level
Postdoc
Field of study
Computer Science
Funding
Full-time postdoctoral appointment for two years. Salary is 300,000–360,000 RMB per year depending on expertise. The position includes a complementary health insurance scheme in addition to social security. No teaching duties.
Deadline
Dec 30, 2026
Country
China
University
Beihang University

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About this position
Beihang University’s Computational Physics & Data Science Research Group at the Hangzhou International Innovation Institute is inviting applications for postdoctoral positions in Deep Learning, Data Assimilation, and Turbulence.
The role is a full-time two-year postdoc with 2 positions available. The salary is 300,000–360,000 RMB per year, depending on the candidate’s expertise. There are no teaching duties.
Applicants should have defended their PhD less than 3 years before the job offer date and hold a PhD in Computational Fluid Dynamics, Deep Learning/Data Assimilation, or a related field. Strong programming skills in Fortran, C++ or Python are required, along with experience in high-fidelity computation and analysis of turbulence or the application of deep learning/data assimilation methods in Fluid Mechanics or Aerodynamics.
The position is based in Hangzhou, China. The group describes the environment as international and equitable, and offers a complementary health insurance scheme plus social security, as well as flexible working arrangements.
To apply, email your CV and covering letter to [email protected]. The cover letter should explain your interest and suitability for the post, and the CV should include your publication list. Applications are open until 2026-12-30.
Funding details
Full-time postdoctoral appointment for two years. Salary is 300,000–360,000 RMB per year depending on expertise. The position includes a complementary health insurance scheme in addition to social security. No teaching duties.
What's required
Applicants should have defended their PhD thesis less than 3 years before the job offer date. A PhD in Computational Fluid Dynamics, Deep Learning, Data Assimilation, or a related field is required. Candidates should be proficient in Fortran, C++, or Python and have experience with high-fidelity computation and analysis of turbulence or with deep learning/data assimilation methods in fluid mechanics or aerodynamics.
How to apply
Send your CV and covering letter by email to [email protected]. Include a cover letter describing your interest and suitability for the post and a full CV with your publication list.
More information can be found here
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