- Analyze energy storage applications
- Characterize energy storage test data
- Develop optimization algorithms to make energy storage decisions (e.g., sizing, location, dispatch, etc.)
- Apply machine learning techniques to optimize the use of energy storage for grid applications
- Publish research in conference and journal publications
- Ph.D. in Mathematics or a related field with a focus on energy applications and machine learning
- Coursework or experience with optimization methods and their application in electric power systems
- Coursework or experience with energy storage and grid applications
- Strong programming skills with scripting languages like Python, R, MATLAB, etc.
- Machine learning coursework or experience
- Database coursework or experience
- Demonstrated publication record
- Excellent verbal and written communication skills
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Postdoctoral Appointee - Albuquerque, United States - Sandia National Laboratories
Description
What Your Job Will Be Like:
We are seeking a postdoctoral appointee to perform research on energy storage analytics with a specialization in machine learning.
On any given day, you may be called on to:
Due to the nature of the work, the selected candidate must be able to work onsite at the Sandia Albuquerque location.
Qualifications We Require:
Qualifications We Desire:
