Overview

The Electricity Infrastructure and Buildings Division of PNNL is accelerating the transition to a decarbonized, efficient, resilient, and secure energy system through basic and applied research. We leverage a strong technical foundation in power and energy systems and in advanced data analytics to drive innovation, transform markets, and shape energy policy.

This position will provide support to the Laboratory’s research in Optimization and Control of Energy Systems. This position will focus on research at the intersection of controls, learning, and computing with an emphasis on data driven and learning based control methods for enhancing the efficiency of energy systems including the electric power grid, buildings, and transportation systems. A successful candidate will be required to conduct independent research, develop new ideas and contribute to research proposals, engage with business development managers in relevant areas, prepare manuscripts for publication, and present their work to clients and at conferences.

Responsibilities

• Providing technical input on large, complex, formal documents, such as project reports, lead author on journal articles, conference papers, and presentations.

• Selecting and developing technical approaches to project work assignments.

• Contributing to technical proposals for developing new projects and business.

• Working with senior staff and project managers to develop and implement project management plans for moderate to large projects.

• Working in a team environment of high-performance multi-disciplinary experts.

• Accountable to team leader, group leader and project managers for project development, execution, and closure.

Qualifications

Minimum Qualifications:

• BS/BA and 2 years of relevant experience -OR-

• MS/MA -OR-

• PhD

Preferred Qualifications:

• Strong technical background in statistical methods, reinforcement learning, uncertainty quantification.

• Good understanding of and interest in advanced grid modeling techniques, renewable energy systems, and energy policy.

• Research experience in demand response, energy storage and other distributed energy resources.

• Proficiency in python, R, and excel.

• Familiar with existing deep learning libraries (e.g., TensorFlow, PyTorch, Caffe2) and machine learning packages (i.e. sklearn).

• Experience applying machine and deep learning or statistical methods to domain specific applications, such as buildings and power grid.

Hazardous Working Conditions/Environment

Not applicable.

Testing Designated Position

This is not a Testing Designated Position (TDP).

About PNNL

Pacific Northwest National Laboratory (PNNL) is a world-class research institution powered by a highly educated, diverse workforce committed to the values of Integrity, Creativity, Collaboration, Impact, and Courage. Every year, scores of dynamic, driven people come to PNNL to work with renowned researchers on meaningful science, innovations and outcomes for the U.S. Department of Energy and other sponsors; here is your chance to be one of them!

At PNNL, you will find an exciting research environment and excellent benefits including health insurance, flexible work schedules and telework options. PNNL is located in eastern Washington State—the dry side of Washington known for its stellar outdoor recreation and affordable cost of living. The Lab’s campus is only a 45-minute flight (or 3-hour drive) from Seattle or Portland, and is serviced by the convenient PSC airport, connected to 8 major hubs.

Commitment to Excellence, Diversity, Equity, Inclusion, and Equal Employment Opportunity

Our laboratory is committed to a diverse and inclusive work environment dedicated to solving critical challenges in fundamental sciences, national security, and energy resiliency. We are proud to be an Equal Employment Opportunity and Affirmative Action employer. In support of this commitment, we encourage people of all racial/ethnic identities, women, veterans, and individuals with disabilities to apply for employment.

Pacific Northwest National Laboratory considers all applicants for employment without regard to race, religion, color, sex (including pregnancy, sexual orientation, and gender identity), national origin, age, disability, genetic information (including family medical history), protected veteran status, and any other status or characteristic protected by federal, state, and/or local laws.

We are committed to providing reasonable accommodations for individuals with disabilities and disabled veterans in our job application procedures and in employment. If you need assistance or an accommodation due to a disability, contact us at careers@pnnl.gov .

Drug Free Workplace

PNNL is committed to a drug-free workplace supported by Workplace Substance Abuse Program (WSAP) and complies with federal laws prohibiting the possession and use of illegal drugs.

If you are offered employment at PNNL, you must pass a drug test prior to commencing employment. PNNL complies with federal law regarding illegal drug use. Under federal law, marijuana remains an illegal drug. If you test positive for any illegal controlled substance, including marijuana, your offer of employment will be withdrawn.

HSPD-12 PIV Credential Requirement

In accordance with Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, new employees are required to obtain and maintain a HSPD-12 Personal Identity Verification (PIV) Credential. 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.

Mandatory Requirements

Please be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from having any affiliation with the foreign government of a country DOE has identified as a “country of risk” without explicit approval by DOE and Battelle. If you are offered a position at PNNL and currently have any affiliation with the government of one of these countries, you will be required to disclose this information and recuse yourself of that affiliation or receive approval from DOE and Battelle prior to your first day of employment.

Rockstar Rewards

Employees and their families are offered medical insurance, dental insurance, vision insurance, health savings account, flexible spending accounts, basic life insurance, disability insurance, employee assistance program, business travel insurance, tuition assistance, supplemental parental bonding leave, surrogacy and adoption assistance, and fertility support. Employees are automatically enrolled in our company funded pension plan and may enroll in our 401k savings plan. Employees may accrue up to 120 vacation hours per year and may receive ten paid holidays per year.

• Research Associates excluded.

**Once eligibility requirements are met.

Click Here For Rockstar Rewards (https://careers.pnnl.gov/rockstar-rewards)

Notice to Applicants

PNNL lists the full pay range for the position in the job posting. Starting pay is calculated from the minimum of the pay range and actual placement in the range is determined based on an individual’s relevant job-related skills, qualifications, and experience. This approach is applicable to all positions, with the exception of positions governed by collective bargaining agreements and certain limited-term positions which have specific pay rules.

As part of our commitment to fair compensation practices, we do not ask for or consider current or past salaries in making compensation offers at hire. Instead, our compensation offers are determined by the specific requirements of the position, prevailing market trends, applicable collective bargaining agreements, pay equity for the position type, and individual qualifications and skills relevant to the performance of the position.

Minimum Salary

USD $109,400.00/Yr.

Maximum Salary

USD $174,800.00/Yr.