The CEI Graduate Fellowship at the University of Washington supports exceptional doctoral researchers focused on clean energy solutions. This fellowship aims to cultivate the next generation of leaders and innovators in the field. Fellows will conduct original research, develop science communication skills, and engage in professional development and outreach activities to enhance public understanding of clean energy issues. The fellowship particularly encourages applications that integrate artificial intelligence (AI), machine learning, and high-throughput approaches into clean energy research, whether by applying existing AI/ML expertise or by adopting new data-driven methodologies. The program emphasizes research excellence, leadership potential, and active participation within the Clean Energy Institute (CEI) community.
The fellowship aims to prepare and empower students to become future leaders and innovators in the clean energy sector, making meaningful societal impacts through technology transfer, commercialization, education, public outreach, science communication, and mentorship.
Research project should align with CEI's core areas: solar energy, energy storage, energy systems, advanced materials & measurements. Demonstrated student merit through accomplishments, leadership, and service at UW is a key factor. Priority given to students demonstrating potential for a meaningful pivot to AI/ML or data-driven methods in clean energy.
Fellows may hold other fellowships but CEI funding will not increase pay beyond standard departmental RA salary. No materials, supplies, or equipment are provided.
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The fellowship provides RA salary and tuition support for two quarters. Specific amounts are tied to departmental rates and no materials, supplies, or equipment are provided.
You must be a current PhD student who began doctoral study between June 1, 2023, and September 30, 2025, have an advisor, and not plan to graduate before September 30, 2027. Incoming first-year students are ineligible.
The application deadline is May 1st for the following academic year. Decisions are typically announced in early June.
The fellowship focuses on clean energy solutions and particularly encourages applications integrating AI, machine learning, and high-throughput approaches. Relevant research areas include solar energy, energy storage, energy systems, and advanced materials & measurements.
You will need to submit an application form, a statement of purpose, and two letters of recommendation.