Brookhaven National Laboratory delivers discovery science and transformative technology to power and secure the nation's future. Primarily supported by the U.S. Department of Energy's (DOE) Office of Science, Brookhaven Lab is a multidisciplinary laboratory with seven Nobel Prize-winning discoveries, 37 R&D 100 Awards, and more than 70 years of pioneering research.
Brookhaven is operated and managed by Brookhaven Science Associates, which was founded by the Research Foundation for the State University of New York on behalf of Stony Brook University, and Battelle, a nonprofit applied science and technology organization.
The IS Department, in collaboration with others, is performing research in the areas of Smart Grid development and grid integration of renewable energy generation. The goal of our research is to contribute to the development of the next generation Smart Grid, including applications of innovative Smart Microgrid technology that could form the building blocks of the distribution portion of the grid. One project the successful candidates will support is to identify cascading failure mechanisms and develop a data-driven, deep learning-based solution to prevent the propagation of cascading failures when the grid is challenged by unexpected contingencies or combinational contingencies under uncertain environments.
The Interdisciplinary Science (IS) Department at Brookhaven National Laboratory (BNL) is seeking a Postdoctoral Research Associate to perform research in the areas of Smart Grid development and grid integration of renewable energy generation.
This position will be a two-year term appointment, reporting to the Renewables and Grid Analysis Group Leader, Robert Lofaro.
Essential Duties and Responsibilities:
Work with other researchers on the project team in support of various studies and programs, including grid modeling and analysis
Statistical data analyses
Probabilistic planning and writing reports on the analysis results
Required Knowledge, Skills, and Abilities:
PhD in electrical engineering with broad knowledge of electric power systems and a strong background in machine learning applications in the power grid.
Experience with nonlinear system analysis and control synthesis, modeling electrical networks with integrated renewable energy sources
Python and/or Matlab programming.
Effective written and oral communication skills.
Ability to work with others as part of a project team.
BNL policy requires that research associate appointments be made to individuals who have received their doctorate within the past five years.
Preferred Knowledge, Skills, and Abilities:
Experience with data analytics and statistics background as well as tools such as Hardware-in-loop simulators, PSS/E, PSCAD, or OpenDSS
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
At Brookhaven National Laboratory we believe that a comprehensive employee benefits program is an important and meaningful part of the compensation employees receive. Our benefits program includes, but is not limited to:
Paid Parental Leave
Swimming Pool, Weight Room, Tennis Courts, and many other employee perks and benefits
Brookhaven National Laboratory and the Energy and Photon Sciences Directorate are committed to your success. We offer a supportive work environment and the resources necessary for you to succeed.
We invite you to consider Brookhaven National Laboratory for employment. To be considered for this position, please apply online at BNL Careers and enter the job title into the Keyword Search.
Brookhaven National Laboratory (BNL) is an equal opportunity employer that values inclusion and diversity at our Lab. We are committed to ensuring that all qualified applicants receive consideration for employment and will not be discriminated against on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, status as a veteran, disability or any other federal, state or local protected class.
BNL takes affirmative action in support of its policy and to advance in employment individuals who are minorities, women, protected veterans, and individuals with disabilities. We ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
*VEVRAA Federal Contractor
Internal Number: 2111
About Brookhaven National Laboratory
Brookhaven National Laboratory is a multipurpose research institution funded primarily by the U.S. Department of Energy’s Office of Science. Located on the center of Long Island, New York, Brookhaven Lab brings world-class facilities and expertise to the most exciting and important questions in basic and applied science—from the birth of our universe to the sustainable energy technology of tomorrow. We operate cutting-edge large-scale facilities for studies in physics, chemistry, biology, medicine, applied science, and a wide range of advanced technologies. The Laboratory's almost 3,000 scientists, engineers, and support staff are joined each year by more than 4,000 visiting researchers from around the world. Our award-winning history, including seven Nobel Prizes, stretches back to 1947, and we continue to unravel mysteries from the nanoscale to the cosmic scale, and everything in between. Brookhaven is operated and managed by Brookhaven Science Associates, which was founded by the Research Foundation for the State University of New York on behalf of Stony Brook University, and Battelle, a nonprofit applied science and technology organization.