Postdoctoral Appointee – Machine Learning for Power System
- Argonne National Laboratory
- Location: Lemont, USA
- Job Number: 7195256 (Ref #: 416857)
- Posting Date: 3 months ago
Job Description
The Advanced Grid Modeling group at Argonne National Laboratory's Center for Energy, Environmental, and Economic Systems Analysis is looking for a dedicated Postdoctoral Researcher. This role is ideal for someone passionate about advancing the integration of distributed energy resources (DER) and renewable energy into the power grid. The selected candidate will be involved in applying state of the art machine learning and deep learning algorithms to develop cybersecurity, optimization, and control solutions for transmission and distribution system operators.
Job duties but not limited to:
Develop ETL pipelines to ingest multi-modal time series data for ML model training.
Develop ML models using CNN, LSTM, and Transformer architectures for applications like anomaly detection, time series forecasting, and surrogate models.
Design and implement game theory and reinforcement learning-based solutions for power grid control problems or cybersecurity applications.
Conduct research and development in federated learning applications for distributed grid management and control.
Perform exploratory data analysis and generate analytics from power grid measurements.
Collaborate with multidisciplinary teams to develop innovative solutions and technologies for complex challenges in energy systems and power grid domains.
Present research findings through seminars, journal articles, technical reports, and at conferences and workshops.
Contribute to open-source software development initiatives for Department of Energy projects.
Position Requirements
Ph.D. in Computer Science, Electrical Engineering, Operations Research, or a related field.
Solid foundation in mathematics/statistics with experience in cyber-physical systems modeling and analysis.
Proficiency in Python.
Proficiency in scripting using at least one ML framework (Keras, TensorFlow, or PyTorch).
Ability to work both independently and collaboratively in a team environment.
Demonstrated experience in interdisciplinary research.
Proven problem-solving and analytical skills.
Strong communication skills, both oral and written.
Record of publications in high-impact journals and experience in proposal development.
Alignment with Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork.
Preferred Qualifications:
Working knowledge of electric power transmission and distribution systems, DER operations, and grid modeling and simulation.
Experience in developing ML solutions using reinforcement learning and/or Transformer architecture.
Familiarity with AutoML, federated learning, and game theoretic modeling.
Familiarity with power system analysis software such as MATPOWER, PSS/E, OpenDSS or similar.
Job Family
Postdoctoral FamilyJob Profile
Postdoctoral AppointeeWorker Type
Long-Term (Fixed Term)Time Type
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