Post-doctoral Fellowships in Machine Learning/Numerical Analysis in Geotechnical Engineering at Shandong University

Post-doctoral Fellowship positions in Machine Learning/Numerical Analysis in Geotechnical Engineering are open at the Geotechnical Engineering Research Group, Shandong University, Jinan, China. Candidates should have graduated with a Ph.D. within the last three years and have experience in machine learning/numerical analysis in geotechnical engineering. Successful candidates will engage in interdisciplinary research in applying machine learning/numerical analysis in transportation geotechnics or offshore geotechnical engineering. Interested applicants are encouraged to contact Prof. Kai Yao https://www.researchgate.net/profile/Kai-Yao by emailing yaokai@sdu.edu.cn

The salary package could be referred to https://www.en.sdu.edu.cn/info/1169/7271.htm

The Required Qualifications:

  • Legal Compliance: Candidates must comply with Chinese laws and regulations, be physically and mentally healthy, and have no criminal record,
  • Age Requirement: Must be 35 years old or younger,
  • Educational Background: Must hold a Ph.D. in Geotechnical Engineering, Civil Engineering, Geological Engineering, or a closely related field, obtained within the last three years, or be on track to complete their Ph.D. soon,
  • Commitment: Must be able to conduct a full-time postdoctoral research at Shandong University,
  • Experience in numerical analysis in geotechnical engineering,
  • Proficiency in programming with Python, MATLAB, or Fortran.

The Application Process:

  • Application Materials:
    1. CV (with a list of publications)
    2. 1-page cover letter (please explain how you fit into this position; please also clearly indicate in the letter that you meet the requirements for points 2 and 3 listed under ‘The Required Qualifications.’)
  • How to Apply: Email your application materials to Prof. Yao at yaokai@sdu.edu.cn
  • Deadline: Nov 31, 2024 (Only shortlisted candidates will be contacted)
  • Starting date for the position: at the earliest convenience.

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