Post-Doctoral Researcher: Air Quality
Post-Doctoral Researcher: Air Quality
CO - Golden
Postdoc (Fixed Term)
Hours Per Week
Working at NREL
The National Renewable Energy Laboratory (NREL), located at the foothills of the Rocky Mountains in Golden, Colorado is the nation's primary laboratory for research and development of renewable energy and energy efficiency technologies.
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The National Renewable Energy Laboratory’s (NREL’s) Strategic Energy Analysis Center (SEAC; www.nrel.gov/analysis ) is seeking a Post-doctoral researcher with strong programming experience who can, under supervision and mentorship, independently lead more than one project within a growing portfolio of air quality, public health and environmental justice-related projects.
The analyst will join the Impacts Analysis Group within SEAC, alongside researchers who perform environmental sustainability assessments of energy technologies. With objective, technology-neutral analysis, SEAC aims to increase understanding of energy policies, markets, resources, technologies, and infrastructure to address U.S. economic, security, and environmental priorities. SEAC researchers employ a wide range of advanced modeling methods and tools to assess the impacts of energy technologies, including air quality, public health and environmental justice models and tools as well as code-based lifecycle assessment (LCA) models.
SEAC, in partnership with other Centers at NREL, is being asked to quantify the air quality impacts and benefits of energy technologies in a range of domestic and international contexts. We seek applicants interested in a diverse set of source sectors and project applications, interested in developing new air quality/impact methods as well as developing innovative computational solutions.
Several bodies of work exist at NREL with emissions inventory, air quality modeling, health impact analysis and environmental justice foci. One body of work focuses on assessing the impact of power system transformation on air quality, collaborating with NREL’s core capability in power sector modeling from decadal to sub-minute timescales (see, e.g., https://www.nrel.gov/analysis/electric-sector-integration.html ). For this work, we work both domestically and internationally. We employ reduced complexity air quality models (like InMAP, as well as its global version, Global InMAP), source-specific models (like R-Line or SCICHEM) and are waiting for the right opportunity to use traditional, state-of-the-science air quality models (like WRF-Chem or CMAQ). Our projects examine a range of spatial scales from multi-country regions (like SE Asia), national and metropolitan. A flagship example of this modeling is the air quality, health and environmental justice portions of LA100 (see Chapters 9 and 10 here ). Another emerging body of work focuses on use of hydrogen in combustion systems (e.g., to replace natural gas in combustion turbines for peaking loads). Our international portfolio is also growing (see a fact sheet ). A good example of a completed project examined the air quality and health implications of greater use of renewable energy in the power sector of Southeast Asia. Finally, we have been characterizing emissions from the supply chain of biofuels for many years (https://www.nrel.gov/analysis/biofuels-emissions.html ).
NREL has advanced scientific computing capabilities within its Energy Systems Integration Facility . Applicants are sought that can bring our emerging air quality modeling capability to the next level with machine learning and advanced computing to answer challenging questions at greater spatial, temporal and global scales.
The ideal candidate will have competency in using a wide range of computer tools, programming languages (e.g., Python, R, Fortran) and shell scripting (bash, C shell), as well as demonstrated experience in atmospheric and air quality modeling. Experience with machine learning and advanced computing (e.g., high-performance computing environment) to answer challenging questions at greater spatial, temporal, and global scales is highly desirable. Also desirable is an interest in adjacent disciplines and fields such as life cycle assessment, greenhouse gas inventories, air pollution measurement, citizen science, atmospheric sciences, etc. Knowledge of at least one energy sector (e.g., power, transportation) will be considered a plus.
The candidate should have strong written communication skills, interest in leading drafting of publications; be highly motivated and self-directed; eager to join a fast-paced collaborative work environment; have an ability to “manage up”; and be available to start by fall 2023.
Basic QualificationsMust be a recent PhD graduate within the last three years.
* Must meet educational requirements prior to employment start date.
Additional Required Qualifications
- Programming skills related to working with quantitative data analysis, such as experience in energy modeling and programming, knowledge of machine learning and advanced computing, fluency in Python or similarly functional language, and ability to quickly pick up other languages
- Advanced experience running a range of air quality models, tools, and databases, including developing code-based workflows. While we use reduced-complexity air quality models, we would prefer candidates who also have experience with more advanced models that include ozone chemistry, secondary PM formation, oxides of nitrogen, etc.
- Emission processing tools and software such as SMOKE, MOVES
- Knowledge of air pollution control engineering
- Excellent oral and written communication and recordkeeping skills, including the ability to give clear oral presentations on progress and results.
- The ability to work independently within a team environment.
- Self-motivated learner with demonstrated ability to grasp new concepts quickly and to develop new skills and models as needed.
- A strong publication record in a technical discipline, as compared to peers at a similar level of education and career experience
- Interdisciplinary curiosity and resourcefulness, including desire to broaden skills.
- Creative problem solving and robust analytical skills, particularly as they relate to facilitating the energy transition through co-beneficial strategies
- Interpersonal and communication skills for interacting with both technical and non-technical audiences.
- Knowledge of statistical methods and GIS tools (ArcGIS/QGIS, or geospatial data analysis libraries in python or R)
- Experience with version control software (GitHub)
Annual Salary Range (based on full-time 40 hours per week)Job Profile: Postdoctoral Researcher / Annual Salary Range: $71,300 - $117,600
NREL takes into consideration a candidate’s education, training, and experience, expected quality and quantity of work, required travel (if any), external market and internal value, including seniority and merit systems, and internal pay alignment when determining the salary level for potential new employees. In compliance with the Colorado Equal Pay for Equal Work Act, a potential new employee’s salary history will not be used in compensation decisions.
Benefits include medical, dental, and vision insurance; short-term disability insurance*; pension benefits*; 403(b) Employee Savings Plan with employer match*; life and accidental death and dismemberment (AD&D) insurance; personal time off (PTO) and sick leave; and paid holidays. NREL employees may be eligible for, but are not guaranteed, performance-, merit-, and achievement- based awards that include a monetary component. Some positions may be eligible for relocation expense reimbursement.
* Based on eligibility rules
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