Dr. Su Jiang is looking for 1-2 motivated Ph.D. students to join her research group in the
Department of Civil and Environmental Engineering at Carnegie Mellon University, starting
in Spring or Fall 2026. Our group focuses on advancing scientific machine learning, data
assimilation, and decision making for environmental fluid mechanics, with applications in
energy, water, and Earth system sciences. The research topics cover:
- Data-driven and physics-informed machine learning for eSicient predictions of
multi-physics systems involving flow, geomechanics, and thermal dynamics. - Data assimilation and uncertainty quantification using multi-scale, multi-source
observations for large-scale subsurface flow systems. - Decision-making under uncertainty for monitoring and injection planning for closedloop reservoir management.
Applications involve subsurface energy and groundwater systems such as geological
carbon storage, geothermal energy, seawater intrusion, and contaminant transport.
Candidate requirements: - B.S. or M.S. in Civil/Environmental Engineering, Hydrogeology, Mechanical
Engineering, Data Science, Applied Math, or related fields. - Strong interests in subsurface flow and machine learning.
- Prior experience in AI/ML, numerical simulation, or inverse problems.
- Strong programming skills in scientific computing.
What we o3er: - Full financial support, including tuition, stipend, benefits.
- Opportunities for interdisciplinary collaboration.
How to apply:
The positions are expected to start in Spring/Fall 2026. Please send an email to
sujiang@andrew.cmu.edu with the subject line “PhD Application – [Your Name]”. Include
your CV, transcripts, a brief introduction of your background, research experience and
interests
About the Author
