The Seismic Wave Analysis Group (SWAG) led by Tariq Alkhalifah has openings for two postdoctoral researchers with a background in wave-propagation related inverse problems (Geophysics, Optics), or applied Mathematics (Optimization and/or Machine Learning).

The candidate is expected to work on topics supporting:

  • Seismic imaging and inversion with full waveforms
  • ML-assisted seismic imaging applications

The candidate will be encouraged to:

  • Develop methods to tackle waveform inversion challenges
  • Utilize machine learning algorithms in improving waveform imaging and inversion.
  • Work with a team attitude, which includes interaction with fellow researchers and students.
  • Interact with teams within KAUST.
  • Develop her/his own qualification in Machine Learning and HPC.
  • Learn and grow as a scientist.
  • Participate in major international conferences.

The initial contract will be offered for 2-years.

The position includes:

  1. A competitive to top US market salary
  2. Furnished housing on KAUST campus provided
  3. Medical and dental insurance provided
  4. Annual paid vacation
  5. Sponsored yearly flights to the home country
  6. Access to the private beach on the Red Sea and other KAUST recreation facilities
  7. Relocation allowance of US$3,000


  1. PhD degree in a related field
  2. Initial software development experience (Python, C, C++ are preferred)
  3. Ability to efficiently communicate in English

Additional (optional) qualifications:

  1. Publication(s) in top scientific journals
  2. Familiarity with HPC (MPI, OpenMP, CUDA)
  3. Experience in seismic multiparameter inversion (elasticity, anisotropy)
  4. Experience in advanced machine learning (GANs, Bayesian methods…)
  5. Strong analytical skills related to wave propagation
  6. Experience in teaching and writing research grant proposals

Application Instructions

Application should include

  • CV with a list of publications and research interests.
  • Copy of official academic transcripts.
  • recommendation letter/email from current manager or PhD supervisor.
  • A list of names/affiliations and contact details of at least two potential referees.


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