ORNL: Postdoc: Modeling, Controls, and AI for Thermal Systems

This is a postdoctoral research post at Oak Ridge National Laboratory (requisition 17135). It sits in the Building Equipment Research Group, Buildings and Transportation Science Division, Energy Science and Technology Directorate. The work combines thermal-fluid science, control theory and AI/ML to model, optimize, predict and autonomously control thermal systems such as HVAC, water heating and data center cooling. The appointment is for up to 24 months, with possible extension, and suits recent PhD graduates in thermal-fluid systems and controls.

What you'll do

• Develop physics-based, data-driven and hybrid physics-informed ML models of thermal systems to capture their dynamic behavior
• Validate the models against experimental data and refine their accuracy and computational efficiency
• Design and implement advanced control strategies, such as model predictive, adaptive, feedback/feedforward and ML-based control, for thermal system optimization
• Test control algorithms through simulation, hardware-in-the-loop testing or physical testbeds, and integrate real-time sensor data and telemetry into closed-loop control
• Apply machine learning to predict thermal system performance, detect anomalies and build AI-driven predictive maintenance strategies
• Analyze and improve HVAC, water heating and data center cooling systems at both system and component level

Who can apply

• A PhD in Computer Science, Computer Engineering, Mechanical Engineering, Electrical Engineering or a related field, obtained within the last five years
• All degree requirements must be completed before the appointment starts
• At least 3 years of experience modeling and optimizing complex engineering systems
• A demonstrated understanding of thermal-fluid system architecture, including heat exchangers, compressors, refrigerant cycles and control valves
• Experience in control theory and control system design, in applying ML/AI to engineering systems, and in Python, MATLAB/Simulink and/or TensorFlow or PyTorch
• Preferred: a background in heat transfer or thermal system dynamics, reinforcement learning for real-time control, and hardware-in-the-loop testing. Foreign nationals who have not lived in the U.S. For three years need a Local Site Specific Only risk determination instead of a PIV credential

How to apply

Apply through the ORNL careers site on the listing page, and upload your documents to your candidate profile. Submit two letters of reference, either uploaded with the application or emailed to Postdocrecruitment@ornl.gov with the position title and number in the subject line. The page gives no closing date or selection dates.

Official page: jobs.ornl.gov/job/Oak-Ridge-Postdoctoral-Research-Associate-Modeling%2C-Control%2C-and-AI-for-Thermal-Systems-TN-37830/1431424000/