Postdoctoral Position in Computer Science (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: ???? careers@anl.gov ???? 630-252-2336 Learn more about Argonne’s science and technology: Science & Technology at Argonne If you apply for this position please say you saw it on Computeroxy

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.