Description
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:
- A competitive to top US market salary
- Furnished housing on KAUST campus provided
- Medical and dental insurance provided
- Annual paid vacation
- Sponsored yearly flights to the home country
- Access to the private beach on the Red Sea and other KAUST recreation facilities
- Relocation allowance of US$3,000
Qualifications
- PhD degree in a related field
- Initial software development experience (Python, C, C++ are preferred)
- Ability to efficiently communicate in English
Additional (optional) qualifications:
- Publication(s) in top scientific journals
- Familiarity with HPC (MPI, OpenMP, CUDA)
- Experience in seismic multiparameter inversion (elasticity, anisotropy)
- Experience in advanced machine learning (GANs, Bayesian methods…)
- Strong analytical skills related to wave propagation
- 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.
- A recommendation letter/email from current manager or PhD supervisor.
- A list of names/affiliations and contact details of at least two potential referees.
Apply:
https://apply.interfolio.com/78917
