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NREL is seeking a postdoc to design, train, and analyze the AI/ML and control algorithms for hybrid energy systems including industrial systems, building controls, and advanced energy systems. This will feature integration of technologies such as across generation, storage, and the grid. The postdoc will develop novel AI/ML architectures, training methods and operational strategies for hybrid systems. The researcher will need to deploy scalable strategies for varying hybrid plant sizes in real-time. The researcher will use a variety of simulation tools including, HOPP (Hybrid Optimization and Performance Platform), PSCAD, Simulink, SAM (System Advisory Model), and OpenDSS (an electric power distribution system simulator). This researcher is expected to demonstrate a broad understanding and wide application of engineering principles, theories and concepts as well as general knowledge of hybrid energy related disciplines and applications. The researcher will use a combination of conventional control methods (e.g. model predictive control) and AI/ML methods such as reinforcement learning, differentiable optimization, or differentiable predictive control. The researcher will work with a variety of customers including federal, state, and industry partners. They will also work collaboratively with other national laboratories, industry and the international community and execute hybrid energy related engineering projects worldwide. The successful candidate will have excellent writing, interpersonal and communication skills. The candidate will be expected to help publish results in technical journals/conference proceedings and present work at conferences, symposia, and sponsor review meetings. They will also be expected to support the development of new work proposals, preparations, and reviews.
