Job Location: United States
Posting Title
Graduate (Year-Long) Intern – Neurosymbolic Artificial Intelligence for Energy Systems
Location
CO – Golden
Position Type
Intern (Fixed Term)
Hours Per Week
40
COVID-19 Safety Protocols
Employment at NREL is contingent upon your compliance with all NREL and U.S. Department of Energy (DOE) safety protocols and mitigation efforts directed at the COVID-19 pandemic.
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 eight 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
The AI, Learning and Intelligent Systems (ALIS) Group in the NREL Computational Science Center has an opening for a graduate student researcher to participate in a research project focusing on neurosymbolic and other next-generation AI approaches and their application to the design and control of energy systems.
The researcher’s work schedule may be flexible to accommodate academic workloads (e.g., full-time in the summer, and part-time during the academic year). If academic work is compatible with this research effort, some degree of overlap may be possible. Work may be done remotely, in-person, or both.
The graduate researcher will be a full team member, working closely with other researchers to publish impactful research. The successful candidate will work with a research team to conduct and analyze approaches to AI that combine modern, state of the art neural network-based methods with classical symbolic approaches. We anticipate that the research will involve integrating Artificial Intelligence (AI) techniques, such as reinforcement learning (RL), with classical mathematical optimization approaches and implementations, where symbolic and sub-symbolic representations are freely intertwined, and learning is ubiquitous. Approaches inspired by cognitive science are especially welcome. We seek candidates capable of pursuing research directions that combine these algorithmic components, using implementations that are suitable for effective utilization of the modern parallel computing architectures that are available at NREL. Candidates with creative problem-solving skills, interest in cross-disciplinary collaboration, and a passion for the mission and goals of both NREL and EERE are of particular interest.
Responsibilities
- Participate in collaboration with domain experts to identify where neurosymbolic AI constitutes a viable approach and maintain awareness of such research both at NREL and in the literature more generally.
- Assist in development clean energy-related AI challenges to stimulate collaboration with broader “next-generation” AI community. Adopt existing – or develop new – mathematical, computing, and simulation frameworks required to implement and evaluate novel combinations of neural and symbolic AI.
- Engage in creative identification of new opportunities to leverage neurosymbolic AI to augment or enhance classical optimization algorithms and/or formulations; include existing knowledge extensively and extendably into AI solutions.
- Engage in collaborative development of journal and conference manuscripts, technical papers, and project reports
Basic Qualifications
Must be enrolled as a full-time student in a Bachelor’s, Master’s or PhD degree program, or graduated in the past 12 months from an accredited institution. Internship period cannot exceed 12 months past graduation. Minimum of a 3.0 cumulative grade point average.
Please Note
- You will need to upload official or unofficial school transcripts as part of the application process.
- If selected for position, a letter of recommendation will be required as part of the hiring process.
Additional Required Qualifications
- Familiarity with mathematical and statistical foundations of both neural-based AI (statistical learning) and symbolic AI (reasoning).
- Knowledge of modern neural approaches to AI.
Preferred Qualifications
The most preferred qualification for this role is experience with scalable machine learning frameworks, e.g, PyTorch. Any of the following will be considered a bonus:
- Experience with AI solutions that involve more than neural networks.
- Familiarity with and interest in renewable energy technologies and energy systems integration.
- Experience with cognitive science, esp., how it can inform AI.
- Experience with neurally guided combinatorial optimization.
- Experience with programmatic reinforcement learning.
- Experience with AI based on formal logic.
- Experience with probabilistic programming and graphical models.
- Experience working with knowledge bases and ontologies, esp., systems that learn them from data/experience.
- Familiarity with “concept learning”.
- Familiarity with the challenge of “open systems”.
- Experience working with diverse, inclusive, and cross-disciplinary research teams
Annual Salary Range (based on full-time 40 hours per week)
Job Profile: Graduate I / Annual Salary Range: $40,500 – $64,800
NREL takes into consideration a candidate’s education, training, and experience, as well as the position’s work location, 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; 403(b) Employee Savings Plan with employer match*; and sick leave (where required by law). 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. Internships projected to be less than 20 hours per week are not eligible for medical, dental, or vision benefits.
- Based on eligibility rules
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.
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