Research Engineer - Machine learning applications to power system operations
Role details
Job location
Tech stack
Job description
The Grid Automation and Controls Group of the Power Systems and Engineering Center (PSEC) at the National Laboratory of the Rockies (NLR) is looking for a researcher who has solid background on machine learning (ML)/artificial intelligence (AI) with enough knowledge about power systems. The candidate will work on research projects that use ML/AI to solve power system problems, specially with the focus on Large Language Models (LLM). Ideal candidate is expected to have in-depth knowledge and extensive research experience related to LLM and agentic AI. Ideal candidate should have solid programming skillset and software development experience. Knowledge and experience about power systems is a plus.
Requirements
The ideal candidate should be able to conduct research work with limited guidance from senior researchers, and also collaborate with project PI and other power system researchers from the same project team., Relevant Master's Degree . Or, relevant Bachelor's Degree and 2 or more years of experience . General knowledge and application of engineering technical standards, principles, theories, concepts and techniques. Training in team, task or project leadership responsibilities. Intermediate abilities and knowledge of practices and techniques. Beginning experience in project management. Good writing, interpersonal and communication skills., Must have a MS in computer science, electrical engineering, computer engineering or related fields. Must meet educational requirements prior to employment start date., * Experience in natural language learning, generative AI, large language models, foundation models, etc.
- Strong programming skill
- Experience in using high performance computers, Linux systems
Preferred Qualifications
Preferred Qualifications
- In-depth knowledge in graph neural networks and reinforcement learning
- Proven records of research experience related to power systems and power system optimization
- Have a good fundamental knowledge of neural networks, state-of-the-art learning algorithms, and their applications to complex systems
- Proficiency in using Python and machine learning/reinforcement learning packages
- With strong publication record
Benefits & conditions
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: Researcher II / Annual Salary Range: $76,600 - $126,400
NLR 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*- and long-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; paid holidays; and tuition reimbursement*. NLR 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. Limited-term positions are not eligible for long-term disability or tuition reimbursement.
***** Based on eligibility rules
Badging Requirement
NLR is subject to Department of Energy (DOE) access restrictions. All employees must also be able to obtain and maintain a federal Personal Identity Verification (PIV) card as required by Homeland Security Presidential Directive 12 (HSPD-12), which includes a favorable background investigation.