Postdoctoral Fellow - Subsurface Imaging & Data Analytics

University of Houston; Houston (TX); On-site; USD 90,000 - 130,000; Full time

Job summary

The University of Houston is seeking a highly qualified researcher to advance subsurface imaging, data analytics, and computational science. The candidate will contribute to cross-disciplinary projects at the Sugar Land campus, leading analyses and developing reproducible software for complex datasets.

The role emphasizes strong programming in Python/MATLAB/C/C++ or Julia, collaboration, and clear scholarly communication across teams.

Qualifications

• PhD in Geophysics or closely related field is required.
• Experience with subsurface datasets and seismic data is desirable.
• Strong programming and scientific computing skills in Python, MATLAB, C/C++, or Julia.
• Ability to communicate scholarly research and collaborate across disciplines.

Responsibilities

• Reviews progress and evaluates results of experiments or projects under supervision.
• Recommends changes in research, testing or experimental procedures.
• May be responsible for a highly technical and complex research instrument.
• Reviews and evaluates the effectiveness of personnel.
• Plans for and assigns personnel to projects under control.
• Operates with latitude for unreviewed action.
• Receives general supervision with direction from higher levels when needed.
• Performs other job-related duties as required.

Skills

Geophysics

Subsurface imaging

Data analytics

Computational methods

Physics-informed ML

Statistical learning

Uncertainty quantification

Multimodal data integration

Scientific visualization

High-performance computing

Education

PhD in Geophysics

PhD in Earth Science

PhD in Electrical Engineering

PhD in Applied Mathematics

PhD in Computer Science

PhD in Computational Science

Tools

Python

MATLAB

C/C++

Julia

Job description

The University of Houston is seeking a highly qualified researcher to advance subsurface imaging, data analytics, and computational science. The candidate will contribute to cross-disciplinary projects at the Sugar Land campus, leading analyses and developing reproducible software for complex datasets.

The role emphasizes strong programming in Python/MATLAB/C/C++ or Julia, collaboration, and clear scholarly communication across teams.