Mission:
The Laboratory of Soil Mechanics (LMS) at the Swiss Federal Institute of Technology (EPFL) in Lausanne, is seeking a Ph.D. candidate to support the development of innovative tools for improving representative multi-physical modeling of geological CO2 storage (GCS).
LMS is a research lab directed by Prof. Lyesse Laloui that targets real-world challenges related to climate change, global energy demand, sustainable urban design and construction and safe and environmentally friendly waste disposal systems, through the development of unique analytical tools and innovative technologies.
The objective of this project is to develop a novel methodology through data-driven Machine Learning (ML) approaches for improving successful upscaling of subsurface engineering. A unique dataset from a metre-scale demonstrator of GCS in EPFL will enable fine training of the ML algorithms and the results will be compared to more conventional constitutive modeling approaches. Implementation of physical laws and multi-physics constrains may be considered for evaluating their impact on the accuracy of the results and computational cost. The methodology aims to significantly improve computational time and reliability of multi-scale modeling for the prediction of the macroscopic mechanical behavior of the involved geomaterials in GCS (caprock and reservoir).
The overall approach of the project aims to bridge lab- to field-scales in the context of a wider range of geotechnical/geomechanical subsurface applications (e.g. radioactive waste storage, hydrogen storage, hydrocarbon extraction etc.).
Role and responsibilities:
- Conduct a comprehensive review of existing constitutive models and ML approaches relevant to multi-physical modeling.
- Implement data-driven ML approaches to existing numerical tools and develop innovative numerical methods and design flowcharts.
- Disseminate research output in journals and international conferences.
- Collaborate in research and teaching activities of LMS.
Your profile:
- Master’s degree in Civil Engineering, Applied Mechanics, Physics or related areas.
- Excellent analytical skills and knowledge of at least one programming language (such as Python, C, C++).
- Enthusiastic, ambitious, and with a strong interest in geomechanics.
- Self-driven with strong problem-solving abilities and out-of-the-box thinking.
- Experience in computer programming in relation to either constitutive modeling of soils or application of machine learning techniques to engineering problems is an advantage.
- Excellent English communication skills (oral and written).
We offer:
- Opportunity to work on a competitive and innovative project in a top-ranked engineering school.
- As an EPFL employee, you will work in a stimulating, dynamic, and interdisciplinary environment.
- EPFL is an equal opportunity employer. We offer a competitive salary commensurate with skills and experience and subject to the EPFL pay scale.
More information can be found at the following websites:
Starting date:
As soon as possible
Term of employment:
Fixed-term (CDD)
Duration:
3 to 4 years, depending on the research progress.
Contact:
Please send an email with the subject line “Ph.D. application – SFOE project” including your CV, a motivation statement and transcripts of records (Bachelor’s/Master’s) to [email protected] and [email protected].
Applications will be evaluated in the order they are received. Shortlisted candidates will be invited to apply to one of the EPFL doctoral schools (EDME). This parallel application process is necessary to be eligible for a PhD at EPFL.