Energy Systems Data Science Postdoctoral Researcher

Idaho National Laboratory • Idaho Falls, ID

2d • Onsite

About The Position

The Idaho National Laboratory (INL) is seeking a Postdoctoral Research Associate in electrical engineering, power and energy systems, or a comparable discipline for its Energy and Water Systems Analysis group. The researcher will apply data science, machine learning, optimization, and reliability and risk analysis methods to hydropower, marine energy, and other power system assets, and contribute to software and data tools that support decision-making by the energy industry and research sponsors.

Possible research includes reliability analysis and risk assessment of marine energy technologies; machine-learning-based prediction of dynamic loading on energy infrastructure under icing conditions, with reliability and risk evaluation; and development of an electricity price database and integration of price forecasting into optimization-based valuation tools. The researcher may also support data science and analysis for hydropower technology commercialization and fish passage projects, assessments of non-powered dams, and technical assistance evaluating the techno-economic potential of hybridizing existing hydropower plants with complementary technologies such as energy storage.

The postdoctoral researcher will contribute to an interdisciplinary R&D team, work independently and collaboratively, execute work as directed by project managers and principal investigators, and adapt as funding and priorities change. The position includes writing scientific manuscripts for journal publication, contributing to proposals for continued research funding, and presenting results at conferences and sponsor meetings. The team works a 9x80 schedule at the Idaho Falls facility, with every other Friday off.

Requirements

• PhD in electrical engineering, power and energy systems, industrial/systems engineering, mechanical engineering, data science, operations research, computer science, or another relevant discipline.
• PhD requirements must be completed by the commencement of the appointment and within the previous five years.
• Demonstrated oral and published written communication skills in English.
• Proficiency in Python.
• Experience applying data analytics and machine learning to engineering or energy systems problems.
• Experience with at least one of the following: reliability analysis, risk assessment, or mathematical optimization.

Nice To Haves

• Experience with reliability engineering and quantitative risk assessment methods, such as probabilistic or structural reliability, uncertainty quantification, Monte Carlo simulation, fault tree analysis, or failure mode analysis.
• Experience formulating and solving optimization problems, such as linear, mixed-integer, or stochastic programming, using tools such as Pyomo, Gurobi, or similar.
• Experience in techno-economic analysis of energy projects, including hybrid systems that combine hydropower with energy storage or other generation.
• Experience with hydropower, non-powered dams, fish passage, marine energy, offshore wind, or other energy-water issues.

Responsibilities

• Apply data science, machine learning, optimization, and reliability and risk analysis methods to hydropower, marine energy, and other power system assets.
• Contribute to software and data tools that support decision-making by the energy industry and research sponsors.
• Conduct research that may include reliability analysis and risk assessment of marine energy technologies.
• Develop machine-learning-based predictions of dynamic loading on energy infrastructure under icing conditions and conduct reliability and risk evaluations.
• Develop an electricity price database and integrate price forecasting into optimization-based valuation tools.
• Support data science and analysis for hydropower technology commercialization and fish passage projects, non-powered dam assessments, and technical assistance evaluating hybrid hydropower projects.
• Work independently and as a member of an interdisciplinary R&D team, executing work as directed by project managers and principal investigators.
• Write scientific manuscripts for journal publication, contribute to research funding proposals, and present results at conferences and sponsor meetings.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree