Posting Title
Postdoctoral Researcher – Multi-resolution Transportation and Energy Modeling
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Location
CO - Golden
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Position Type
Postdoc (Fixed Term)
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Hours Per Week
40
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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.
From day one at NREL, you’ll connect with coworkers driven by the same mission to save the planet. By joining an organization that values a supportive, inclusive, and flexible work environment, you’ll have the opportunity to engage through our ten employee resource groups, numerous employee-driven clubs, and learning and professional development classes.
NREL supports inclusive, diverse, and unbiased hiring practices that promote creativity and innovation. By collaborating with organizations that focus on diverse talent pools, reaching out to underrepresented demographics, and providing an inclusive application and interview process, our Talent Acquisition team aims to hear all voices equally. We strive to attract a highly diverse workforce and create a culture where every employee feels welcomed and respected and they can be their authentic selves.
Our planet needs us! Learn about NREL’s critical objectives, and see how NREL is focused on saving the planet.
Note: Research suggests that potential job seekers may self-select out of opportunities if they don't meet 100% of the job requirements. We encourage anyone who is interested in this opportunity to apply. We seek dedicated people who believe they have the skills and ambition to succeed at NREL to apply for this role.
Job Description
Seeking a high-caliber postdoctoral candidate to join our group and to conduct research related to mobility and energy impacts of emerging transportation technologies. Candidates with knowledge and experience in travel demand modeling, travel behavior methods, geospatial analysis, high performance computing, and advanced choice modeling techniques are encouraged to apply. Relevant areas of research the candidate will be working on include: (i) Travel demand modeling, (ii) Econometric and statistical methods for transportation data analysis, (iii) Mobility and energy impacts of disruptive transportation technologies, and (iv) Transportation system efficiency quantification. Prior knowledge in applying traditional (four-step) travel models, and advanced agent-based transportation models is strongly preferred. Application of machine learning techniques to travel behavior modeling is desired. Specific activities may include:
- Working with travel demand models, particularly integrating NREL developed tools such as the Mobility Energy Productivity (MEP) metric, and Route Energy Prediction Model (RouteE) into existing travel demand models.
- Developing travel choice models using traditional (survey) and non-traditional (big-data) sources.
- Perform big data analytics, visualization, and interpretation.
- Working with cloud-based web applications and scalable data analysis pipelines, refactoring data science scripts as cloud-native software.
- Building, enhancing, and validating modeling and simulation tools.
- Assist in producing high-quality publications, reports, and research proposals.
- Supporting additional related research projects as needed.
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Basic Qualifications
Must be a recent PhD graduate within the last three years.
* Must meet educational requirements prior to employment start date.
Additional Required Qualifications
Preferred Qualifications
Highest priority preferred qualifications:
- Familiarity with transportation data and development of travel modeling and forecasting tools.
- Experience with transportation modeling packages such as CUBE, TransCAD, MATSim, or similar tools.
- Strong background with scientific programming languages such as Python, R, Rust, or Scala.
- Strong interest in, and working knowledge of high-performance computing and transportation modeling, with a degree/background in one or the other.
- Relevant transportation skills may include travel demand modeling, micro-, meso- and/or macroscopic traffic modeling, and transportation energy analysis.
- Relevant computational skills may include machine learning, deep learning, distributed computing, and big data management/analytics.
- Familiarity with location-based data, and its use for travel modeling.
- Knowledge of GIS, GPS, data analysis and visualization, web design, and/or engineering computing.
- Strong collaboration skills—thrives working in a collaborative team environment but is comfortable working independently when necessary.
Additional preferred qualifications:
- Excellent verbal and written communication skills.
- Experience with data analytics, big data management, scraping data off the web, high-performance/distributed computing, machine learning and/or deep learning.
- Application development experience in a general-purpose programming language such as C/C++, JavaScript, Java, Scala, or Rust.
- Experience interfacing with Metropolitan Planning Organizations (MPOs) and other transportation data and modeling stakeholders.
- Knowledge of cloud computing services such as AWS, Azure, or Google Cloud.
- Working with HPC and databases, including PostGres, and slurm.
- Experience in transportation and/or computational sciences.
- Experience with collaborative software development and use of Git/GitHub for project management and version control.
- Knowledge of access theory.
- Cumulative undergraduate/graduate GPA over 3.5 on a 4.0 scale.
Please include all relevant experience and qualification information on the uploaded PDF (or MS Word) copy of your resume or CV.
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Job Application Submission Window
The anticipated closing window for application submission is up to 30 days and may be extended as needed.
Annual Salary Range (based on full-time 40 hours per week)
Job Profile: Postdoctoral Researcher / Annual Salary Range: $73,200 - $120,800
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 Summary
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
Drug Free Workplace
NREL is committed to maintaining a drug-free workplace in accordance with the federal Drug-Free Workplace Act and complies with federal laws prohibiting the possession and use of illegal drugs. Under federal law, marijuana remains an illegal drug.
If you are offered employment at NREL, you must pass a pre-employment drug test prior to commencing employment. Unless prohibited by state or local law, the pre-employment drug test will include marijuana. If you test positive on the pre-employment drug test, your offer of employment may be withdrawn.
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.
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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, domestic partner 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.
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