R&D Associate Staff Member - Grid-Interactive Controls Group

Oak Ridge National Laboratory; Knoxville (TN); On-site; USD 90,000 - 130,000; Full time

Job summary

Oak Ridge National Laboratory seeks an R&D Associate focusing on urban-scale energy modeling. You will develop scalable software for building energy models, process large datasets, and create visuals to support planning projects.

The role emphasizes collaboration with multidisciplinary scientists and external stakeholders, with strong written and oral communication. Required is a PhD in a related field, published work, and presentation experience; preferred are AI/ML capabilities for scalable

Qualifications

• PhD in a related field with published work.
• Proven R&D experience in urban-scale building energy modeling or AI/ML.
• Experience with OpenStudio and EnergyPlus modeling.

Responsibilities

• Design, implement, and optimize scalable software for building energy modeling.
• Process large datasets and support data visualization tasks.
• Collaborate with multidisciplinary scientists and external stakeholders.
• Prepare technical solutions, reports, and visuals for planning projects.
• Communicate technical material to scientists and non-scientists.

Skills

Urban-scale energy modeling

Python

AI/ML capabilities

OpenStudio EnergyPlus

Data visualization

Software development

Agile/SCRUM

Geospatial visualization tools

Education

PhD in Mechanical Engineering

PhD in Computer Science

Related field

Tools

ArcGIS

Cesium

AWS

Job description

Requisition Id16177

Overview:

We are seeking an R&D Associate who will focus on urban-scale energy modeling. This position resides in the Grid Interactive Control Group in the Energy Systems Integration section, Electrification and Energy Infrastructure Division, Energy Science and Technology Directorate, at Oak Ridge National Laboratory (ORNL).

Major Duties/Responsibilities:

• Proven R&D experience in urban-scale building energy modeling, software development (esp. Python), or Artificial Intelligence/Machine Learning (AI/ML)
• Strong ideation, writing, and communication skills for establishing ideas and writing proposals that establish new projects
• Understanding for creating, modifying, and analyzing OpenStudio and EnergyPlus building energy models
• Design, implement, and optimize scalable software systems to manage and process large datasets related to building energy modeling and data visualization
• Strong software development skills for automation of many knowledge-based tasks in a version-controlled environment
• Demonstrated teamwork skills for coordinating work of multidisciplinary scientists and in collaboration with external stakeholders
• Project management skills to function well in a fast-paced research environment, set priorities to accomplish multiple tasks within deadlines, and adapt to changing needs
• Prepare technical solutions, reports, and visuals to support a variety of planning project types, including transportation/grid, environmental, community, equity, and sustainability planning
• Excellent communication skills for conveying technical material to both scientists and non-scientists in both written and oral presentations
• Self-disciplined work ethic and eagerness to tackle challenging research problems
• 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

Basic Qualifications:

• A PhD in Mechanical Engineering, Computer Science, or a related field
• Published technical work in journal articles
• Presentation experience at conferences

Preferred Qualifications:

• Experience with applying modern AI/ML capabilities for scalable software development, documentation, usability, and testing
• Create innovative ideas and solutions for urban planning, transportation, and grid integration issues, focusing on resilience
• Monitor and evaluate multi-energy-system integration solutions to ensure they comply with regulations and standards
• Strong strategic planning, community engagement, communication, and public presentation skills
• Establish and maintain relationships with stakeholders and community members to ensure alignment with community needs and goals
• Excellent analytical skills with high attention to detail
• Experience with geospatial data visualization tools such as ArcGIS, Cesium, AWS, or similar.
• Familiarity with urban-scale building energy modeling/analysis
• Experience working in Agile/SCRUM teams
• Excellent written and oral communication skills
• Motivated and conscientious self-starter with the ability to work independently, follow-up on all action items, and 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

Security, Credentialing, and Eligibility Requirements:

For employment at Oak Ridge National Laboratory (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.

To obtain this credential, new employees must successfully complete and pass a Federal Tier 1 background check investigation. This investigation includes a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last year. This includes marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.

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.

About ORNL:

As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy of addressing the nation's most pressing challenges. Our team is made up of over 7,000 dedicated and innovative individuals! Our goal is to create an environment where a variety of perspectives and backgrounds are valued, ensuring ORNL is known as a top choice for employment. These principles are essential for supporting our broader mission to drive scientific breakthroughs and translate them into solutions for energy, environmental, and security challenges facing the nation.

ORNL offers competitive pay and benefits programs to attract and retain individuals who demonstrate exceptional work behaviors. 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.

This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired.

We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be accepted; these resumes will be deleted and the candidates submitted will not be considered for employment.

ORNL is an equal opportunity employer. All qualified applicants, including individuals with disabilities and protected veterans, are encouraged to apply. UT-Battelle is an E-Verify employer.