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Rice University

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Postdoctoral Associate in Machine Learning & Geophysics at Rice University Rice University in United States

Degree Level

Postdoc

Field of study

Computer Science

Funding

Full funding available
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Country

United States

University

Rice University

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Keywords

Computer Science
Mathematics
Seismology
Geophysics
Earth Science
High Performance Computing
Statistics
Physics
ML

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About this position

Rice University’s Department of Earth, Environmental and Planetary Sciences is recruiting a Postdoctoral Associate in Machine Learning & Geophysics with Dr. Ian McBrearty’s lab in Houston, Texas, United States.

The McBrearty Lab works at the intersection of machine learning and physics, developing data-driven methods for earthquake monitoring, processing data from large seismic networks, and building neural-surrogate emulations of PDEs governing tectonic and volcanic processes. The role emphasizes graph neural networks (GNNs), deep learning, scientific computing, and high-performance computing (HPC).

This is a full-time, on-campus postdoctoral position. The university states that the role is funded by a grant and soft and/or restricted funds, with continued employment contingent on renewal of funding. The proposed salary is $65,000.

Applicants should hold a Ph.D. in Geophysics, Computer Science, Data Science, Applied Mathematics, or a related quantitative field. Strong Python skills and experience with deep learning frameworks such as PyTorch or TensorFlow are required, along with excellent communication, organization, and the ability to publish scholarly work. Preferred experience includes GNNs, physics-informed machine learning (PINNs), ObsPy, and large-scale HPC data processing.

Review of applications begins September 1, 2026 and continues until the position is filled. Informal inquiries can be sent to Dr. Ian McBrearty at [email protected]. Apply via the Rice University job portal.

Funding details

Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.

How to apply

Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.

More information can be found here

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