Argonne National Laboratory
Mathematics and Computer Science Division (MCS), Argonne National Laboratory
Location: Argonne, IL
Employment Type: Full-Time, Long-Term (Fixed Term)
Salary Range: $70,758 – $117,925 (DOE guideline)
Position Overview
The Mathematics and Computer Science Division (MCS) at Argonne National Laboratory seeks a Postdoctoral Appointee to conduct cutting-edge research in scientific machine learning, with a focus on developing machine learning-based surrogates and emulators for power grid dynamics.
This role involves:
- Creating probabilistic models that capture the complex behaviors of dynamical systems
- Integrating these models into large-scale optimization frameworks to enhance the efficiency and reliability of power grid operations
- Leading the conceptual design, implementation, and testing of ML models that are trustworthy, scalable, and computationally efficient
- Ensuring accuracy within the operational constraints of real-world power systems on DOE leadership computing facilities
The appointee will work in a collaborative environment across multiple teams to advance research in scientific computing, machine learning, and power systems.
Required Qualifications
- Ph.D. in Computer Science, Electrical Engineering, Applied Mathematics, or related field (completed within the past 0–5 years)
- Strong proficiency in Python; experience in C, C++, or similar languages
- Expertise in machine learning for dynamical systems, particularly those described by differential-algebraic equations
- Experience with high-performance computing and distributed computing environments
- Excellent oral and written communication skills
- Commitment to Argonne’s core values: impact, safety, respect, integrity, and teamwork
Preferred Qualifications
- Experience with power grid modeling and large-scale optimization problems
- Familiarity with ML surrogates and emulators for dynamical systems
- Proficiency in managing large datasets and training on GPU-enabled resources
- Expertise in numerical optimization and ML frameworks (PyTorch, Jax, TensorFlow)
- Strong foundation in statistics, probability theory, or uncertainty quantification
Responsibilities
- Conduct independent research in scientific machine learning for power systems
- Design and implement scalable and accurate ML models for grid dynamics
- Collaborate with multi-disciplinary teams and contribute to joint research efforts
- Publish results in peer-reviewed journals and present at conferences
Benefits
Argonne offers a comprehensive benefits package, including:
- Health, dental, and vision insurance
- Retirement plans
- Paid time off and parental leave
- Flexible schedules and wellness programs
For more details: Argonne Employee Benefits
Equal Employment Opportunity
Argonne National Laboratory is an equal opportunity employer. All qualified applicants are considered without regard to race, color, religion, sex, national origin, disability, veteran status, or other protected characteristics.
Employees may be subject to restrictions related to Foreign Government Sponsored or Affiliated Activities (DOE Order 486.1A) and must disclose any such participation. All offers are contingent on a background check and, if required, government access authorization.
Application Process
Interested candidates should apply through Argonne’s careers site. For assistance with applications or reasonable accommodations:
[contact details available in the full listing]
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Learn more about Argonne’s science and technology: Science & Technology at Argonne
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