Postdoctoral Research Associate - Modeling, Control, and AI for Thermal Systems
Oak Ridge National Laboratory · Oak Ridge, TN · 1 mo ago
AnalystFull-time
We need to output HTML fragment with sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. We must not repeat job title. Must not include Job ID/requisition numbers as headings; can fold minor metadata into short p or drop. Remove boilerplate, navigation, legal, EEO, scam warning, duplicated lines, application instructions. Preserve all substantive info.
We need to parse the posting.
Overview: description of role. That can go under About the role.
Major Duties/Responsibilities: list of duties. Use
- .
Basic Qualifications: list of qualifications. Use
- .
Preferred Qualifications: also qualifications; could be under Qualifications or Skills? The instruction: Use headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. So we need to map content.
- About the role: overview paragraph.
- Responsibilities: Major Duties/Responsibilities.
- Requirements: Basic Qualifications (must-have). Could also include Special Requirements? Those are special requirements like PhD time limit, appointment length, reference letters, PIV etc. Those are requirements as well. Might include them under Requirements.
- Qualifications: Preferred Qualifications.
- Skills: maybe combine technical skills from qualifications? Could list programming languages, tools, etc. But we already have them in qualifications. Could separate: Skills: proficiency in programming, simulation tools, ML frameworks, etc. But we need to avoid duplication? The instruction: Preserve ALL substantive information; do NOT invent or summarize away detail. So we need to include all info, but we can organize under headings. Duplication is okay if it's from different parts? Probably better to not duplicate same content under multiple headings unless it's distinct. We can put technical skills under Skills, and qualifications under Qualifications (education, experience). Let's extract.
Basic Qualifications:
- Ph.D. degree in Computer Science, Computer Engineering, Mechanical Engineering, Electrical Engineering, or related discipline obtained within last five years.
- Minimum 3 years experience in modeling and optimizing complex engineering system.
- Demonstrated understanding of thermal-fluid system architecture, including component-level behavior (heat exchangers, compressors, refrigerant cycles, control valves) and integration into system-level performance.
- Demonstrated experience in control theory and control system design (e.g., model predictive control, feedback control, adaptive control).
- Experience applying machine learning/AI to engineering systems.
- Proficiency in programming and simulation tools such as Python, MATLAB/Simulink, and/or ML frameworks (TensorFlow, PyTorch).
- Experience with physics-based modeling.
- Strong analytical and problem-solving skills, ability to work independently on complex research problems.
Preferred Qualifications:
- Strong background in thermal-fluid sciences, heat transfer, or thermal system dynamics.
- Prior research experience in thermal systems, controls, or AI/ML applications.
- Experience developing and deploying reinforcement learning algorithms for real-time control applications.
- Experience with hardware-in-the-loop (HIL) testing or integrating control algorithms into physical testbeds.
- Knowledge of predictive maintenance methods and anomaly detection techniques for complex systems.
- Experience with sensor networks, IoT platforms, or real-time data acquisition and telemetry systems.
- Familiarity with cloud computing platforms and edge deployment of ML models.
- Experience with uncertainty quantification, sensitivity analysis, or robust optimization methods.
- Track record of publications in relevant journals/conferences (e.g., ASME, IEEE, ASHRAE).
- Excellent written and oral communication skills.
- Motivated self-starter with ability to work independently and to participate creatively in collaborative teams across the laboratory.
- Ability to function well in a fast-paced research environment, set priorities to accomplish multiple tasks within deadlines, and adapt to ever changing needs.
Special Requirements (maybe under Requirements):
- Applicants cannot have received their Ph.D. more than five years prior to date of application and must complete all degree requirements before starting appointment.
- Appointment length up to 24 months with potential for extension; initial appointments and extensions subject to performance and funding.
- Please submit two letters of reference when applying.
- For employment at ORNL, a Real ID compliant form of identification will be required.
- Additionally, ORNL is subject to DOE access restrictions. All employees must also be able to obtain and maintain a federal PIV card as mandated by HSPD-12 and DOE Order 473.1A, which requires a favorable post-employment background investigation.
- To obtain this credential, new employees must successfully complete and pass a Federal Tier 1 background check investigation. This includes declaration of illegal drug activities, including use, supply, possession, or manufacture within last year (including marijuana and cannabis derivatives, still illegal under federal law).
- For foreign national candidates: If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) risk determination to maintain employment. Once you meet the three-year residency requirement, you will be required to obtain a PIV credential to maintain employment.
These are requirements; we can include them under Requirements.
About ORNL: description of lab, benefits, etc. Benefits: list of benefits. Pay: not specified (no salary). So we should NOT create Pay section because no specific pay info. Schedule: not specified (no schedule). So we should not create Schedule section.
Benefits: we have a list: "ORNL offers competitive pay and benefits programs... The laboratory provides a range of employee benefits, including medical and retirement plans and flexible work hours, to support the well-being of you and your family. Employee amenities such as on-site fitness, banking, and cafeteria facilities are also available for added convenience. Other benefits include the following: Prescription Drug Plan, Dental Plan, Vision Plan, 401(k) Retirement Plan, Contributory Pension Plan, Life Insurance, Disability Benefits, Generous Vacation and Holidays, Parental Leave, Legal Insurance with Identity Theft Protection, Employee Assistance Plan, Flexible Spending Accounts, Health Savings Accounts, Wellness Programs, Educational Assistance, Relocation Assistance, and Employee Discounts."
We should include Benefits section with that list.
We must not include boilerplate like equal opportunity, EEO, scam warning, application instructions, etc. Also remove duplicated lines. Also remove navigation/cookie/legal. So we need to strip those.
We need to output only HTML fragment, no /, no markdown fences.
Thus produce something like:
About the role
We are seeking a Postdoctoral Research Associate – Modeling, Controls, and AI for Thermal Systems to advance the design, operation, and maintenance of thermal systems through data-driven modeling and optimization. The successful candidate will work at the intersection of thermal-fluid sciences, control theory, and artificial intelligence/machine learning to advance the design and operation of next-generation thermal systems, developing strategies to model, optimize, predict, and autonomously control thermal systems behavior in complex systems. The candidate will contribute to developing and improving the performance of next-generation thermal systems—including HVAC, water heating, and data center cooling—at both the system and component level. This position resides in the Building Equipment Research Group in the Buildings and Transportation Science Division in the Energy Science and Technology Directorate at Oak Ridge National Laboratory (ORNL).
Responsibilities
- Develop physics-based, data-driven, and hybrid (physics-informed ML) models of thermal systems to capture dynamic thermal behavior
- Validate models against experimental data and refine model accuracy and computational efficiency
- Model thermal system design, operation, and maintenance scenarios to support optimization and decision-making
- Analyze and improve performance of HVAC, water heating, and data center cooling systems
- Work across system-level and component-level design challenges
- Integrate predictive and optimization techniques to enhance system efficiency, reliability, and autonomy
- Design and implement advanced control strategies (e.g., model predictive control, adaptive control, feedback/feedforward control, ML-based controls) for thermal system optimization
- Integrate real-time sensor data and telemetry into closed-loop control frameworks
- Test and validate control algorithms through simulation, hardware-in-the-loop testing, and/or physical testbeds
- Apply machine learning techniques to predict thermal system performance and detect anomalies
- Develop AI-driven predictive maintenance strategies to anticipate system failures or performance degradation
- Use AI/ML methods to optimize thermal system design parameters and operating conditions
- Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service.
- Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success.
- .
Preferred Qualifications: also qualifications; could be under Qualifications or Skills? The instruction: Use headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. So we need to map content.
- About the role: overview paragraph.
- Responsibilities: Major Duties/Responsibilities.
- Requirements: Basic Qualifications (must-have). Could also include Special Requirements? Those are special requirements like PhD time limit, appointment length, reference letters, PIV etc. Those are requirements as well. Might include them under Requirements.
- Qualifications: Preferred Qualifications.
- Skills: maybe combine technical skills from qualifications? Could list programming languages, tools, etc. But we already have them in qualifications. Could separate: Skills: proficiency in programming, simulation tools, ML frameworks, etc. But we need to avoid duplication? The instruction: Preserve ALL substantive information; do NOT invent or summarize away detail. So we need to include all info, but we can organize under headings. Duplication is okay if it's from different parts? Probably better to not duplicate same content under multiple headings unless it's distinct. We can put technical skills under Skills, and qualifications under Qualifications (education, experience). Let's extract.
Basic Qualifications:
- Ph.D. degree in Computer Science, Computer Engineering, Mechanical Engineering, Electrical Engineering, or related discipline obtained within last five years.
- Minimum 3 years experience in modeling and optimizing complex engineering system.
- Demonstrated understanding of thermal-fluid system architecture, including component-level behavior (heat exchangers, compressors, refrigerant cycles, control valves) and integration into system-level performance.
- Demonstrated experience in control theory and control system design (e.g., model predictive control, feedback control, adaptive control).
- Experience applying machine learning/AI to engineering systems.
- Proficiency in programming and simulation tools such as Python, MATLAB/Simulink, and/or ML frameworks (TensorFlow, PyTorch).
- Experience with physics-based modeling.
- Strong analytical and problem-solving skills, ability to work independently on complex research problems.
Preferred Qualifications:
- Strong background in thermal-fluid sciences, heat transfer, or thermal system dynamics.
- Prior research experience in thermal systems, controls, or AI/ML applications.
- Experience developing and deploying reinforcement learning algorithms for real-time control applications.
- Experience with hardware-in-the-loop (HIL) testing or integrating control algorithms into physical testbeds.
- Knowledge of predictive maintenance methods and anomaly detection techniques for complex systems.
- Experience with sensor networks, IoT platforms, or real-time data acquisition and telemetry systems.
- Familiarity with cloud computing platforms and edge deployment of ML models.
- Experience with uncertainty quantification, sensitivity analysis, or robust optimization methods.
- Track record of publications in relevant journals/conferences (e.g., ASME, IEEE, ASHRAE).
- Excellent written and oral communication skills.
- Motivated self-starter with ability to work independently and to participate creatively in collaborative teams across the laboratory.
- Ability to function well in a fast-paced research environment, set priorities to accomplish multiple tasks within deadlines, and adapt to ever changing needs.
Special Requirements (maybe under Requirements):
- Applicants cannot have received their Ph.D. more than five years prior to date of application and must complete all degree requirements before starting appointment.
- Appointment length up to 24 months with potential for extension; initial appointments and extensions subject to performance and funding.
- Please submit two letters of reference when applying.
- For employment at ORNL, a Real ID compliant form of identification will be required.
- Additionally, ORNL is subject to DOE access restrictions. All employees must also be able to obtain and maintain a federal PIV card as mandated by HSPD-12 and DOE Order 473.1A, which requires a favorable post-employment background investigation.
- To obtain this credential, new employees must successfully complete and pass a Federal Tier 1 background check investigation. This includes declaration of illegal drug activities, including use, supply, possession, or manufacture within last year (including marijuana and cannabis derivatives, still illegal under federal law).
- For foreign national candidates: If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) risk determination to maintain employment. Once you meet the three-year residency requirement, you will be required to obtain a PIV credential to maintain employment.
These are requirements; we can include them under Requirements.
About ORNL: description of lab, benefits, etc. Benefits: list of benefits. Pay: not specified (no salary). So we should NOT create Pay section because no specific pay info. Schedule: not specified (no schedule). So we should not create Schedule section.
Benefits: we have a list: "ORNL offers competitive pay and benefits programs... The laboratory provides a range of employee benefits, including medical and retirement plans and flexible work hours, to support the well-being of you and your family. Employee amenities such as on-site fitness, banking, and cafeteria facilities are also available for added convenience. Other benefits include the following: Prescription Drug Plan, Dental Plan, Vision Plan, 401(k) Retirement Plan, Contributory Pension Plan, Life Insurance, Disability Benefits, Generous Vacation and Holidays, Parental Leave, Legal Insurance with Identity Theft Protection, Employee Assistance Plan, Flexible Spending Accounts, Health Savings Accounts, Wellness Programs, Educational Assistance, Relocation Assistance, and Employee Discounts."
We should include Benefits section with that list.
We must not include boilerplate like equal opportunity, EEO, scam warning, application instructions, etc. Also remove duplicated lines. Also remove navigation/cookie/legal. So we need to strip those.
We need to output only HTML fragment, no /, no markdown fences.
Thus produce something like: