Research Professional - Grid Control and Machine Learning

About the role

The Grid Interactive Controls Research Group (GIC) in the Electrification and Energy Infrastructure Division (EEID) within the Energy Science and Technology Directorate (ESTD) at Oak Ridge National Laboratory (ORNL) is seeking a R&D Associate Staff Member.

Responsibilities

• Conduct innovative research on real-time, time-synchronized measurement-to-model approaches for modern power systems with high DER penetration.
• Develop grid-edge sensing and real-time monitoring systems to provide high-resolution measurements for situational awareness, dynamic modeling, and control decisions.
• Design reliable timing and synchronization architectures to ensure distributed grid-edge and substation measurements are time consistent and model ready.
• Integrate grid-edge measurements and system-level observations into unified workflows for DER aggregation and parameter identification.
• Apply machine learning techniques to improve DER/IBR model calibration, parameter estimation, uncertainty assessment, and decision support.
• Build and apply hardware-in-the-loop test platforms to validate the full sensing, timing, modeling, and control under real-time conditions.
• Establish HIL-based test protocols and performance metrics to assess accuracy, latency, and robustness under practical engineering constraints.
• Collaborate with power systems, controls, hardware, and field engineering teams to transition measurement-driven models and real-time prototypes into deployable, control-ready solutions.
• Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success.

Qualifications

• Ph.D. in electrical engineering, power systems, computer engineering, control engineering, or a closely related field.
• Strong background in power system modeling, dynamic simulation, and DER integration.
• Experience with real-time systems, hardware-in-the-loop simulation, or power system testbeds.
• Proficiency in programming and data analysis using tools such as Python, MATLAB, C/C++, or similar languages.
• Ability to develop, validate, and document research prototypes, algorithms, and technical workflows.
• Strong written and verbal communication skills for interdisciplinary research and engineering collaboration.

Preferred Qualifications

• Experience with grid-edge sensing, synchronized measurements, PMU/POW data, or distribution-level monitoring systems.
• Experience with reliable timing, time synchronization or timing-error impact analysis.
• Experience with DER model aggregation, parameter identification, model reduction, or dynamic equivalent modeling.
• Experience with power system simulation and modeling tools such as PSCAD, PSSE, OpenDSS, MATLAB/Simulink, or similar platforms.
• Hands-on experience with real-time simulation or hardware-in-the-loop platforms such as OPAL-RT, RTDS, Typhoon HIL, or similar systems.
• Familiarity with software coding and hardware development in the context of power systems research.
• Proven track record of scholarly publications and presentations in relevant fields.
• Experience in proposal writing.

Special Requirements

• Security, Credentialing, and Eligibility Requirements: For employment at ORNL, a Real ID compliant form of identification will be required. Additionally, ORNL is subject to Department of Energy (DOE) access restrictions. All employees must also be able to obtain and maintain a federal Personal Identity Verification (PIV) card as mandated by Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which requires a favorable post-employment background investigation.