Postdoctoral Fellow in the DeepWave Consortium
The DeepWave Consortium at King Abdullah University of Science and Technology (KAUST) is recruiting two postdoctoral researchers for an industry-funded project focused on machine learning for wave-equation-based processing, imaging, and inversion.
The postdoctoral fellow will join the research group of Prof. Tariq Alkhalifah in the Earth Systems Science and Engineering (ESSE) program at KAUST, Saudi Arabia, and will work closely with group members on methods that combine physics and machine learning for geophysical applications. The research direction includes machine-learning-assisted subsurface characterization and monitoring, distributed acoustic sensing (DAS) data processing and compression, and physics-driven machine learning for geophysical modeling and inversion.
The role is intended for candidates with a PhD, or those about to complete one, in geophysics, computational geophysics, applied mathematics, physics, computer science, or a related area. Applicants should have a strong publication record or relevant publication portfolio, good Python programming skills, and proficiency in Torch and/or JAX. A solid understanding of wave phenomena and geophysical data analysis and imaging is expected. Preference is given to candidates with experience in seismic processing algorithms, high-performance computing, large-scale inverse problems, open-source software development, collaborative coding practices, and machine/deep learning.
Successful candidates are expected to initiate and deliver high-quality research, validate methods on field data, contribute to the consortium code base, publish in leading journals, and present work at international conferences. The position is based at KAUST in Thuwal, Saudi Arabia, within the Physical Science and Engineering Division.
Applications are submitted via the provided Interfolio link. The posting does not specify a deadline date.
