PhD Intern - Energy Systems Engineering

At PNNL, our core capabilities are divided among major departments that we refer to as Directorates within the Lab, focused on a specific area of scientific research or other function, with its own leadership team and dedicated budget.  

Our Science & Technology directorates include National Security, Earth and Biological Sciences, Physical and Computational Sciences, and Energy and Environment. In addition, we have an Environmental Molecular Sciences Laboratory, a Department of Energy, Office of Science user facility housed on the PNNL campus. 

The Energy and Environment Directorate delivers science and technology solutions for the nation’s biggest energy and environmental challenges. Our more than 1,700 staff support the Department of Energy (DOE), delivering on key DOE mission areas including: modernizing our nation’s power grid to maintain a reliable, affordable, secure, and resilient electricity delivery infrastructure; research, development, validation, and effective utilization of renewable energy and efficiency technologies that improve the affordability, reliability, resiliency, and security of the American energy system; and resolving complex issues in nuclear science, energy, and environmental management. 

The Electricity Infrastructure and Buildings Division, part of the Energy and Environment Directorate, is accelerating the transition to an efficient, resilient, and secure energy system through basic and applied research. We leverage a strong technical foundation in power and energy systems and advanced data analytics to drive innovation, transform markets, and shape energy policy.

Responsibilities

The Energy Systems Engineering Group is looking for a university intern to work with a team of senior engineers to create high-impact solutions for electric power grids. The intern will come up with creative new solutions to real-world cross-domain data analytics and utilize machine learning problems. The intern will take initiative to identify opportunities to contribute, communicate their questions and results, find solutions to ambiguously defined problems, create reusable software tools, and write research papers during the internship.

Qualifications

Minimum Qualifications:

• Candidates must be currently enrolled/matriculated in a PhD program at an accredited college.
• Minimum GPA of 3.0 is required.

Preferred Qualifications:

• Ph.D. candidates in electrical engineering, math, operations research, statistics, mechanical engineering, and computer engineering/science, with demonstrated training/internship and/or publications in power system analysis.
• Strong written and verbal communication skills.
• Previous project experience creating concrete results both while working independently and with a team.
• Detail-oriented in executing solutions while able to articulate how their work contributes to a larger, impactful effort.
• Preference for multi-domain research background in the energy sector, such as grid, weather forecasting.
• Will need machine learning and statistical inference with applications, experience with PyTorch, TensorFlow etc.
• Will need strong programming skills in Python, MATLAB.
• Knowledge and experience with optimization techniques such as linear and mixed integer linear programming. Experience with optimization software such as GAMS/Pyomo/Cplex and Gurobi.