Berkeley Lab’s () Energy Geosciences Division (EGD) has an opening for a Postdoctoral Researcher in Machine Learning for Geological Carbon Storage to join the team.
In this exciting role, you will join a vigorous team of geoscientist and ML researchers from leading US institutions developing next generation tools for geological carbon storage (GCS).
This role requires ability to develop both novel techniques as well as robust implementation of existing ML approaches into a collaborative software framework.
The initial phase of the project will focus on time-lapse seismic monitoring and target integration of diverse sources of information (seismic images, microearthquake monitoring, borehole geophysics and laboratory measurements) to produce plume images and detect seismogenic faults with high risk of reactivation.
The project will emphasize understanding of the following three aspects : (1) assimilation of heterogeneous input data; (2) issue of scales for seismic wave propagation and multiphase fluid flow;
3) models for different sources of noise in the geophysical data.
What You Will Do :
Development of physics-informed ML models for seismic data interpretation and upscaling of petrophysical measurements.
Analysis of geophysical data to design computer simulations and generate realistic synthetic geophysical data sets.
Collaboration with the Berkeley Lab’s partners on setting up coupled multiphase fluid flow and geomechanical modeling workflows.
Implementation of the ML algorithms in a distributed version control system following the development guidelines.
Work collaboratively with geophysicist, civil engineers, earth scientist, stakeholders to test and demonstrate the functionality of the developed ML systems.
Publish in high quality, peer reviewed journals.
Participate in writing grant applications as well as lead their own proposals.
What is Required :
PhD in Geophysics or related field.
Demonstrated experience with ML tool development, links to released models / software would be great.
First-hand experience with reservoir monitoring and application of physics-based data analysis tools to seismic data, well logs and petrophysical laboratory experiments.
Demonstrated experience with software development and analysis tools, such as GitLab, Linux, Bash / Csh, Python, and Matlab.
More advanced coding skills is an advantage.
Competence in high-performance computing.
Experience in developing numerical models in collaborative environments.
Excellent written, oral, and visual communication skills, demonstrated through prior peer-reviewed publications and presentations at major conferences.
Notes :
This is a full-time, 2 years, postdoctoral appointment with the possibility of renewal based upon satisfactory job performance, continuing availability of funds and ongoing operational needs.
You must have less than 3 years of paid postdoctoral experience. Salary for Postdoctoral positions depends on years of experience post-degree.
The monthly salary range for this position is $7,455 - $8,326 and is expected to start at $7,455 or above. Postdoctoral positions are paid on a step schedule per union contract and salaries are predetermined based on postdoctoral step rates.
Each step represents one full year of completed post-Ph.D. postdoctoral and / or related research experience.
This position is represented by a union for collective bargaining purposes.
This position may be subject to a background check. Any convictions will be evaluated to determine if they directly relate to the responsibilities and requirements of the position.
Having a conviction history will not automatically disqualify an applicant from being considered for employment.
Work will be primarily performed at Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA
Postdoctoral Researcher in Machine Learning for Geological Carbon Storage | Lawrence Berkeley National Laboratory
Berkeley Lab's ( LBNL ) Energy Geosciences Division (EGD) has an opening for a Postdoctoral Researcher in Machine Learning for Geological Carbon Storage to join the team. In this exciting role, you will join a vigorous team of geoscientist and ML researchers from leading US institutions developing n...
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