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Three post-doctoral positions: artificial intelligence for subsurface carbon sequestration planning
The Stanford Center for Earth Resources Forecasting has received funding for a 6-year project to build artificial intelligence for optimal planning of carbon sequestration operations in Eastern Europe. Our project will develop a state-of-the-art Intelligent Agent by formulating sequential decision problems, such as planning CCS operations, as Partially Observable Markov Decision Processes (POMDPs) and developing practical solution methods in a real-world setting that can address the speed and urgency of needing to store CO2 in the subsurface. The goal of this project is to enable better decision making around how, where and at what rate to inject, what monitoring data to plan for safeguarding against induced seismicity and leakage. This aim is for this research to be implemented by a collaborating company by 2030, thereby contributing to the net-zero 2050 challenge.
Because of the breadth and potential impact of this project, we are putting together a large team of students, post-docs and faculty. We are currently seeking to hire three post-doctoral candidates in the following areas:
• Optimization and decision making under uncertainty
• Modeling and numerical simulation of coupled fluid flow and geomechanics in subsurface formation with uncertainty quantification
• Geophysical and other monitoring systems for subsurface fluid flow.
• Excellence in research as demonstrated through publications in scientific journals.
• Experience with real field case studies, not necessarily CCS.
• Computer skills either using commercial or open-source software in the area of decision making under uncertainty, or, computational physics and scientific programming in areas related to fluid flow and fluid-structure interactions, or, geophysical modeling and inversion.
• Demonstrated skills in python or similar scripting languages (e.g. Julia).
• Demonstrated skills in collaborative research.
We are seeking candidates who are quick learners with demonstrated collaborative skills in real world settings, with real case studies. Being able to work in high-energy interdisciplinary teams, and excellent presentation skills are important. We are also looking for candidates with computer science development skills beyond using standard commercial software.
Send a CV, statement, and a list of three referees to email@example.com
In your statement, please elaborate explicitly on the following questions
● Which of the three areas are you applying for
1) Optimization and Decisions
2) Flow Modeling and UQ
3) Geophysical monitoring.
● What real field cases have you been involved with?
● What is your level of programming as provided through examples?