Energy System Control Engineer- Learning Based
Job Description
This position will provide support to the Laboratory’s research in Optimization and Control of Energy Systems. This position will focus on research at the intersection of controls, learning, and computing with an emphasis on data driven and learning based control methods, distributed and robust optimization algorithms for building and power system applications. A successful candidate will be required to conduct independent research, develop new ideas and contribute to research proposals, engage with business development managers in relevant areas, prepare manuscripts for publication, and present their work to clients and at conferences.
The candidate will serve as a technical expert and task lead on multiple significant projects or tasks. This will include:
- Performing independently the activities assigned under the direction and guidance of the project manager, by selecting and developing technical approaches to project work assignments.
- Leading portions of large, complex, formal documents, such as project reports, journal articles, conference papers, and presentations.
- Contributing to technical proposals for developing new projects and business.
- Working with senior staff and project managers to develop and implement project management plans for projects of various sizes.
- Working in a team environment of high-performance multi-disciplinary experts
Key Responsibilities:
- Providing technical input and lead portions of large, complex, formal documents, such as project reports, lead author on journal articles, conference papers, and presentations.
- Selecting and developing technical approaches to project work assignments.
- Working with senior staff and project managers to develop and implement project management plans for moderate to large projects.
- Working in a team environment of high-performance multi-disciplinary experts.
- Accountable to technical group manager and project managers for project development, execution, and closure.
Minimum Qualifications
- Bachelor’s degree with 2 years of experience, MS/MA with 0 years of experience or PhD with 0 years of experience.
Preferred Qualifications
- Strong technical background in distributed control and optimization, machine learning, uncertainty quantification
- Strong understanding of power systems operation, dynamics, and control
- Research experience in demand response, energy storages and other distributed energy resources, renewable energy, microgrid, buildings and their integration to grid.
- Proficiency in python, Julia, C++, Java
- Strong analytical, task management, and communications skills, both oral and written, and able to communicate clearly the goals, parameters, objectives and outcomes of their research