We use cookies. Find out more about it here. By continuing to browse this site you are agreeing to our use of cookies.
#alert
Back to search results

Post Doctoral Research Associate - Grid Controls

Oak Ridge National Laboratory
life insurance, parental leave, 401(k), retirement plan, relocation assistance
United States, Tennessee, Oak Ridge
1 Bethel Valley Road (Show on map)
Nov 19, 2024

Requisition Id12615

Overview:

The Grid Modeling and Controls (GMC) Group 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 Post Doctoral Research Associate to perform R&D in the areas of high-penetration or all power electronics grid modeling, stability analysis, and control design. Selection will be based on qualifications, relevant experience, skills, and education. The successful candidate should be highly self-motivated and independent in conducting research under general guidance, and is expected to prepare manuscripts for scientific publication and present the work to sponsors and at conferences.

The GMC Group supports the energy security and prosperity mission of the Energy Department (DOE) through transformative science and technology solutions, including research supporting the Office of Electricity (OE), Office of Cybersecurity, Energy Security and Emergency Response (CESER) and Office of Energy Efficiency and Renewable Energy (EERE) on the integration of new technologies, identifying and validating new ways of using existing and emerging grid assets to ensure grid reliability, grid resilience, environmental stewardship, and affordability of energy supplies. The GMC group focuses on dynamic grid modeling, analysis, and control R&D specifically related to power electronics-based devices, develops and designs new grid devices deploying new theory and methodologies, and conducts system operation and control R&D of all power electronics grids.

Major Duties/Responsibilities:

  • Develop and advance the state-of-the-art smart inverter control functionalities.

  • Develop new methodologies and algorithms to address future grid control challenges.

  • Develop analytical tools for stability analysis studies of future power grids with high-penetration power electronics.

  • Develop inverter impedance modeling and characterization using different methodologies.

  • Develop new methodology for large-scale power grid system decomposition, simulation and analysis.

  • Develop and verify new methods and algorithms and publish research outcomes.

Basic Qualifications:

  • A Ph.D. degree in Electrical Engineering within the last 5 years.

  • Expertise in inverter impedance modeling, small-signal and large-signal stability analysis.

  • Expertise in advanced inverter controls (e.g. grid-forming, grid-following) and grid supporting (during abnormal or fault conditions).

  • Experience in Matlab, C/C++ and Python programming.

Preferred Qualifications:

  • Experience is using machine learning for grid applications.

  • Strong mathematic skills and knowledge of graph or complex network theory.

  • Understanding of power systems operation and control framework.

  • Excellent written and oral communication skills

  • Motivated self-starter with the 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:

Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements before starting their appointment.

The appointment length will be up to 24 months with the potential for extension. Initial appointments and extensions are subject to performance and availability of funding.

Letters of Recommendation: 3 letters of references are required.

Please submit three letters of reference when applying to this position. You may upload these directly to your application or have them sent to recruiting@ornl.gov with the position title and number referenced in the subject line.

Instructions to upload documents to your candidate profile:

  • Login to your account via jobs.ornl.gov

  • View Profile

  • Under the My Documents section, select Add a Document

Benefits at ORNL:

ORNL offers competitive pay and benefits programs to attract and retain talented people. The laboratory offers many employee benefits, including medical and retirement plans and flexible work hours, to help you and your family live happy and healthy. Employee amenities such as on-site fitness, banking, and cafeteria facilities are also provided for convenience.

Other benefits includethe 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.

If you have difficulty using the online application system or need an accommodation to apply due to a disability, please email: ORNLRecruiting@ornl.gov or call 1.866.963.9545.

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.

If you have trouble applying for a position, please email ORNLRecruiting@ornl.gov.

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.

Applied = 0

(web-5584d87848-7ccxh)