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PhD Fellowship in Energy Systems and Artificial Intelligence

University of Stavanger · Department of Energy and Petroleum Engineering · Norway

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About this position

The University of Stavanger invites applicants for a position as PhD Fellow in Energy Systems and Artificial Intelligence at the Faculty of Science and Technology, Department of Energy and Petroleum Engineering.

The PhD fellowship leads to a doctoral degree and gives you the opportunity to develop research expertise in an active and stimulating academic environment. Through the doctoral education, you will acquire knowledge, skills and experience that qualify you for a further career in research, higher education, and other knowledge-intensive sectors.

The successful candidate will be admitted to the PhD programme in Science and Technology. The programme includes coursework, an independent research project culminating in a doctoral thesis, participation in national and international research communities, dissemination of research, a trial lecture, and a public defence of the thesis. For more information about the PhD education at UiS, please visit

our website.

The position is for three years of pure research training.

As a PhD Fellow at UiS, you will receive supervision and support for your academic and professional development through mentoring, skills development, and career planning.

Research Topic

We are seeking highly motivated and talented candidates for a PhD position at the intersection of Energy Systems and Applied Artificial Intelligence (AI). As the urgency of addressing climate change continues to grow, innovative solutions that reduce emissions, improve energy efficiency, and support sustainable energy systems are more important than ever.

This PhD project focuses on the development of fast, accurate, and robust models for the real-time optimization and control of energy systems, with shallow geothermal energy as a central research area. The project will investigate how AI-driven modeling, system integration, and advanced operational strategies can enhance the performance, efficiency, and flexibility of modern energy systems.

Research Environment and Infrastructure

The successful candidate will have the opportunity to work with cutting-edge energy technologies at the University's Energy Central, a unique living laboratory for research, development, and demonstration of sustainable energy solutions.

Energy Central includes:

120 geothermal boreholes, including 10 dedicated research wells equipped with different borehole heat exchanger designs

Two large-scale commercial heat pumps, each with a heating capacity of 1.3 MW

A research-scale heat pump utilizing supercritical CO₂ as the working fluid, serving as a testbed for data generation, system analysis, and methodology development

Three gas-fired boilers and two electric boilers

Thermal energy storage in the form of a hot-water accumulator

Dry coolers and associated energy infrastructure

This advanced facility is equipped with state-of-the-art monitoring and measurement systems, providing high-quality data for the development and validation of digital twins and AI-based models for techno-economic optimization of integrated energy systems.

A key objective of the project is to incorporate forecasting methods and external data sources, including weather conditions, electricity prices, fuel costs, and emission pricing, to support intelligent and economically optimal system operation.

Why Join This PhD Project?

This PhD position provides a unique opportunity to conduct high-impact research in a highly applied environment, utilizing state-of-the-art energy infrastructure and extensive real-world operational data. The project combines advanced AI methodologies with practical energy-system challenges, offering excellent opportunities for academic development, industrial collaboration, and contribution to the green energy transition.

If you are passionate about sustainable energy systems and eager to apply artificial intelligence to solve real-world energy challenges, we encourage you to apply.

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