Advanced Energy Systems - Colorado School of Mines & NLR

Machine Learning Engineer

• Design, develop, and rigorously test software applications and components
• Apply best practices and cutting-edge technologies to support mission-critical research projects
• Work across the research-to-implementation stack, including designing and evaluating AI models
• Translate research findings into production-ready systems
• Formulate and reason about constrained optimization problems
• Support computational science research involving high-performance computing, AI/ML, modeling and simulation, and visualization
• Collaborate with peers, mentors, team members, DOE program offices, defense and intelligence communities, federal agencies, universities, and industry partners
• Perform technical tasks independently and adapt to different project needs
• Support multiple projects and assist junior-level researchers and developers
• Contribute to technical publications and proposal writing

ML Optimization Engineer

Researcher

• Develop statistical and machine learning techniques and associated software to characterize, model, and fuse multiple sources of information
• Characterize disruptive events and their impacts on infrastructure such as power grids
• Evaluate and communicate research results through written reports and presentations
• Participate in group meetings and seminars
• Assist in engineering and writing statistics and deep learning software
• Conduct statistical and probabilistic data analysis
• Design algorithms and develop publications
• Draft and publish technical reports, conference papers, and journal publications
• Attend and present research at technical conferences
• Collaborate with multidisciplinary research teams, industry, academia, and other national laboratories

Post-doctoral Researcher – Statistical Learning and Modeling

• Conduct research on the future of the U.S. power system
• Support model design and code development for long-term energy systems planning and analysis
• Focus on energy demand forecasting, end-use-sector load profiles, equipment stock turnover, and end-use technology adoption modeling
• Contribute to advanced methods for capacity expansion modeling
• Research power system planning and operation rules, trends, and issues
• Execute quality control methods
• Research, acquire, organize, and analyze large datasets
• Develop flexible data architectures for infrastructure systems
• Collaborate with analysts on other modeling teams to relate model inputs and outputs
• Execute scenarios and analyze and interpret results for reporting
• Communicate results internally and externally
• Write and publish analyses in peer-reviewed journals and technical reports
• Assist in developing proposals for new work

ML Optimization Engineer

Post-doctoral Researcher – Statistical Learning and Modeling

Postdoctoral Researcher – Power Systems Modeling and Analysis