Within this framework, a faculty position in AI-Enabled Modeling and Optimization of Energy Systems is available in the Mechanical Engineering Program.
This position covers the applications of artificial intelligence and data-driven methods to understand, design, and optimize complex energy systems and devices. Example topics include physics-informed machine learning, digital twins for turbines and reactors, AI-driven design of energy hardware, predictive maintenance of energy infrastructure, and data-driven modeling of fluid and thermal systems.
About KAUST and the PSE Division
KAUST is an international graduate research university dedicated to advancing science and technology through interdisciplinary research, education, and innovation. Ranked #1 in the Times Higher Education Arab University Rankings for three consecutive years (2023-2025), KAUST is recognized globally for the quality and impact of its research. Located in Saudi Arabia, on the western shores of the Red Sea, KAUST offers superb research facilities, generous baseline research funding, and internationally competitive salaries, together with comfortable living conditions for individuals and families. More information about KAUST's academic programs and research activities is available at https://www.kaust.edu.sa. The PSE Division comprises five Programs: Chemical Engineering, Chemistry, Earth Systems Science and Engineering, Materials Science and Engineering & Applied Physics, and Mechanical Engineering. More information about the PSE Division is available at https://pse.kaust.edu.sa.
Qualifications
- Ph.D. degree.
- Track record of research excellence demonstrated by impactful publications or industrial experience demonstrated by intellectual property and product development.
- Excellent oral and written English communication skills.
- Ability to establish and lead a rigorous research program.
Application Instructions
Applicants must complete an online application (https://www.kaust.edu.sa/en/about/faculty-positions) via the Interfolio online application system by uploading the following materials:
- Cover letter.
- C.V. including a publication list.
- Research plan (must not exceed 5 pages including references).
- Teaching statement (must not exceed 2 pages including references).
- Contact reference of at least five potential referees (name, affiliation, and e-mail).
- The five most relevant publications.
- Web of Science, Scopus, or Google Scholar citation report.
Apply now: https://apply.interfolio.com/189806
