Postdoctoral Researcher – Building Control and Machine Learning

NATIONAL RENEWABLE ENERGY LABORATORY
NATIONAL RENEWABLE ENERGY LABORATORY

Job Overview

**Posting Title**Postdoctoral Researcher – Building Control and Machine Learning.**Location**CO – Golden.**Position Type**Postdoc (Fixed Term).**Hours Per Week**40.**Job Description**NREL has an immediate opening for a Postdoctoral Researcher in Building Control and Machine Learning.The candidate will join a highly interdisciplinary team and conduct cutting-edge research on building-to-grid integration and advanced data analytics. The candidate will collaborate with a team of engineers, scientists, and software developers to model high-performance buildings and communities, develop novel control and machine learning algorithms for building-grid integration and renewable energy integration, and perform large-scale simulations of future grid-connected communities/districts on NREL’s high-performance computing systems.Responsibilities include (but are not limited to):+ Develop control-oriented, multi-physics models and novel algorithms for holistic integration of buildings, grid, and transportation+ Execute major projects as a key technical contributor independently as well as in a team environment+ Contribute to funding proposal development in the area of building-to-grid integration, sensors and controls, system integration, cyber-physical systems, etc.+ Publish results in peer-reviewed journals, conference proceedings, and/or technical reports; present work at conferences, symposia, and review meetingsThe successful candidate will be an integral part of the Residential Buildings Research Group under the Buildings and Thermal Sciences Center (BTSC) at NREL. BTSC supports the science and technology goals of the U.S. Department of Energy and NREL toward a sustainable energy future.**Required Experience and Skills:**Successful candidates will have qualifications in the following categories:+ Strong background in modeling, simulation, and control of buildings and energy systems (such as battery storage and thermal storage)+ Machine learning experience with building- or energy-related applications such as end-use forecasting, load disaggregation, occupancy prediction, etc.+ Excellent programming and data analytic skills in MATLAB/Simulink, Python, R, or similar languages+ Excellent writing, interpersonal and communication skills.**Basic Qualifications**Must be a recent PhD graduate within the last three years..**Additional Required Qualifications****Preferred Qualifications**Ideal candidates will have a background and expertise in one or more of the following topics:+ Solid background in control theory and prior research experience with model predictive control, stochastic control, distributed/hierarchical control, or transactive control+ Deep understanding and demonstrated experience with classical machine learning techniques as well as reinforcement learning, deep learning, or transfer learning with applications in energy system controls+ Experience with resilient operation of building energy systems and microgrid+ Experience with control-oriented modeling of building systems and related techniques (e.g., system identification, model order reduction)+ Demonstrated experience with building energy simulation tools such as EnergyPlus/BEopt/OpenStudio and co-simulation tools+ Strong optimization skills and hands-on experience with convex and mixed-integer programming tools+ Basic knowledge of power systems and experience with power system simulation software (e.g., OpenDSS, GridLAB-D)+ Experience with embedded systems and debugging in Linux/Unix environment+ Working knowledge of data visualization tools and version control software+ Good track record on peer-reviewed publications and strong interest in authoring high-impact journal articles.**Submission Guidelines**Please note that in order to be considered an applicant for any position at NREL you must submit an application form for each position for which you believe you are qualified. Applications are not kept on file for future positions. Please include a cover letter and resume with each position application..**EEO Policy**NREL is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws.**EEO is the Law** at http://www.dol.gov/ofccp/regs/compliance/posters/ofccpost.htm | **Pay Transparency Nondiscrimination** at https://www.dol.gov/ofccp/pdf/pay-transp_English_unformattedESQA508c.pdf | **Reasonable Accommodations** at http://www.nrel.gov/careers/employment-policies.html**E** **-Verify** **www.dhs.gov/E-Verify** **|For information about right to work, click** **here** at http://www.justice.gov/sites/default/files/crt/legacy/2013/08/13/FinalOSCPosterEN08_01_2013.pdf **for English or** **here** at http://www.justice.gov/crt/file/813271/download **for Spanish.**E-Verify is a registered trademark of the U.S. Department of Homeland Security. This business uses E-Verify in its hiring practices to achieve a lawful workforce.The National Renewable Energy Laboratory (NREL) is a leader in the U.S. Department of Energy’s effort to secure an environmentally and economically sustainable energy future. With locations in Golden and Boulder, Colorado, and a satellite office in Washington, D.C., NREL is the primary laboratory for research, development, and deployment of renewable energy technologies in the United States.NREL is subject to Department of Energy (DOE) access restrictions. All candidates must be authorized to access the facility per DOE rules and guidance within a reasonable time frame for the specified position in order to be considered for an interview. DOE rules for site access during the interview process are the same regardless of whether the candidate is interviewed on-site, off-site, or via telephone or videoconference. Additionally, DOE contractor employees are prohibited from participating in certain Foreign Government Talent Recruitment Programs (FGTRPs). If a candidate is currently participating in an FGTRP, they will be required to disclose their participation after receiving an offer of employment and may be required to disengage from participation in the FGTRP prior to commencing employment. Any offer of employment is conditional on the ability to obtain work authorization and to be granted access to NREL by the Department of Energy (DOE). We understand that COVID-19 may have caused delays or closures at offices, consulates, and embassies. However, NREL cannot make exceptions to work authorization and access requirements, and exceptions to these requirements are not being made for COVID-19 related delays.Please review the information on our Hiring Process at https://www.nrel.gov/careers/hiring-process.html website before you create an account and apply for a job. We also hope you will learn more about NREL at https://www.nrel.gov/about/ , visit our Careers site at https://www.nrel.gov/careers/ , and continue to search for job opportunities at https://nrel.wd5.myworkdayjobs.com/NREL at the lab.

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