⛔ This position is no longer available.
University: ETH Zurich
Country: Switzerland
Deadline: Not specified
Fields: Power Engineering, Computer Science, Electrical Engineering, Artificial Intelligence, Data Science
Topic: Switzerland – PhD in Foundation Models for Power Grids at ETH Zurich
Fields: Power Engineering, Computer Science, Electrical Engineering, Artificial Intelligence, Data Science
Position: PhD
Country: europe
Deadline: Not specified
University: ETH Zurich
Real Country: Switzerland
Main Category: engineering
—
Are you passionate about driving the future of sustainable energy systems through advanced artificial intelligence and machine learning? Do you envision yourself at the forefront of research that integrates power engineering with cutting-edge computational methods to address the pressing challenges of climate change and the energy transition? At ETH Zurich, you have the unique opportunity to embark on a fully funded PhD project developing next-generation AI foundation models for the electric power grid—an endeavor poised to reshape the backbone of tomorrow’s energy infrastructure.
About the University or Research Institute
ETH Zurich (Swiss Federal Institute of Technology in Zurich) stands as one of the world’s leading universities for science and technology. Located in the heart of Switzerland’s largest city, ETH Zurich is globally recognized for its pioneering research, outstanding teaching, and strong international orientation. With a tradition of academic excellence dating back to 1855, the university has produced over 20 Nobel laureates, including Albert Einstein, and consistently ranks among the top universities worldwide.
The university’s commitment to innovation, sustainability, and inclusivity makes it a vibrant hub for scholars from across the globe. ETH Zurich’s campus boasts state-of-the-art research facilities, a collaborative interdisciplinary environment, and a thriving student community. The city of Zurich itself is renowned for its high quality of life, safety, and cosmopolitan culture, offering a stimulating setting for both academic and personal growth.
Switzerland, at the crossroads of Europe, is celebrated for its stability, multiculturalism, and leadership in scientific research and sustainability. As a student at ETH Zurich, you will benefit from the nation’s strong support for research and education, as well as its dynamic links to industry and innovation.
Research Topic and Significance
The global energy landscape is undergoing a rapid transformation, driven by the urgent need to mitigate climate change and transition towards renewable energy sources. These changes present unprecedented challenges for the operation, control, and planning of electric power systems. Increasing shares of both centralized and distributed renewables introduce complexity and uncertainty, pushing traditional power grid management approaches to their limits.
This PhD project addresses these challenges by focusing on the development of scalable foundation models (FMs) for the electric power grid, known as GridFM. Foundation models, based on advanced AI architectures such as transformers and self-supervised learning, have revolutionized fields like computer vision and natural language processing. Their application to power systems promises to enable robust, generalizable, and efficient solutions for a wide range of grid-related tasks.
The significance of this research lies in its potential to deliver AI-driven tools that can adapt across multiple power system tasks—from real-time operations and planning to risk assessment—thereby supporting the secure and sustainable transition of energy systems. By collaborating with industry partners and leveraging ETH Zurich’s expertise, the project aims to bridge the gap between theoretical advances and practical implementation, contributing directly to the reliability, resilience, and decarbonization of future energy networks.
Project Details
The PhD project is based within ETH Zurich’s interdisciplinary research environment, specifically at the RRE (details available through the official advertisement link). The main objectives are:
– To develop scalable AI foundation models (GridFM) for the electric power grid.
– To fine-tune these models for diverse downstream tasks relevant to grid operations, planning, and risk analysis.
– To assess the real-world applicability of these models in cooperation with industry stakeholders.
Key research questions include:
– Identifying the most promising machine learning concepts for GridFM, including physics-informed learning, neural operators, and reinforcement learning (RL).
– Exploring the mixture of experts (MoE) paradigm, as exemplified by recent advances in transformer architectures, to enhance model scalability and inference efficiency.
– Determining which power system tasks will benefit most from GridFM, and developing synthetic and real-world datasets for robust model training and evaluation.
The candidate will have access to state-of-the-art computational resources, ongoing collaborations with leading industry partners such as IBM, and a dynamic international research team. The project will utilize existing tools like the PowerGraph dataset and the Cascades modeling platform, with opportunities to contribute to their further development.
Candidate Profile
This position is ideally suited for candidates who are eager to work at the intersection of power engineering and artificial intelligence. Suitable applicants will have:
– An MSc degree (or near completion) in Power Engineering, Computer Science, Electrical Engineering, or a related field.
– A strong quantitative background in either power system analysis or machine learning (expertise in both is advantageous, but not mandatory).
– Experience with programming languages such as Python and familiarity with data-driven modeling approaches.
– A passion for interdisciplinary research, strong analytical and problem-solving skills, and the ability to work independently within a collaborative environment.
– Excellent written and spoken English proficiency.
Candidates should be motivated to contribute to the development of sustainable, reliable, and intelligent energy systems while engaging with a diverse, international research community.
Application Process
ETH Zurich offers a fully funded PhD position with a competitive salary and access to cutting-edge research infrastructure. The university values diversity, equality of opportunity, and sustainability, fostering an inclusive environment where all members can thrive.
To apply, please submit your application exclusively through the ETH Zurich online application portal. Required documents include:
– Curriculum Vitae (CV)
– Cover Letter
– Transcripts from Bachelor’s and Master’s studies
Applications submitted via email or postal services will not be considered.
For further details about the position and to access the application portal, please visit the official advertisement:
https://www.jobs.ethz.ch/job/view/11467
Conclusion
This is a unique opportunity for highly motivated researchers to contribute to the transformation of global energy systems through advanced AI and machine learning. If you are driven by curiosity and a desire to make a tangible impact on the future of power grids and sustainability, ETH Zurich offers the perfect environment to launch your academic career.
Interested candidates are encouraged to apply promptly and explore similar opportunities in the field of power engineering and artificial intelligence.
Questions & Answers
Question: What makes ETH Zurich a leading choice for PhD studies in engineering and AI?
ETH Zurich is consistently ranked among the world’s top universities for science and engineering, with a strong tradition of research excellence, interdisciplinary collaboration, and innovation. Its location in Switzerland offers access to a vibrant academic and industrial ecosystem.
Question: What are foundation models, and why are they important for power systems?
Foundation models are large-scale AI models trained using self-supervised learning on vast datasets, enabling them to generalize across multiple tasks. Their application to power systems can help manage complexity, enhance reliability, and accelerate the integration of renewable energy.
Question: Which backgrounds are suitable for this PhD position?
Applicants with an MSc in Power Engineering, Computer Science, Electrical Engineering, or related fields, and with strong quantitative and programming skills, are encouraged to apply. Experience in machine learning or power systems is highly valued.
Question: What is the working environment like at ETH Zurich?
ETH Zurich offers a dynamic, international, and interdisciplinary research environment, with access to state-of-the-art facilities and a collaborative team culture. The university values diversity, inclusion, and sustainability.
Question: Are there opportunities to collaborate with industry partners?
Yes, the project includes collaboration with industry stakeholders such as IBM, providing real-world relevance and opportunities for practical impact.
Question: How should I submit my application?
All applications must be submitted through the ETH Zurich online application portal as specified in the official job advertisement. Applications via email or post are not accepted.
Question: Is the position fully funded?
Yes, the PhD position is fully funded, with a competitive salary in line with ETH Zurich’s standards.
Question: What are the benefits of studying and living in Switzerland?
Switzerland offers a high quality of life, safety, multiculturalism, and a strong emphasis on research and education. Zurich is a cosmopolitan city with excellent public transport, cultural attractions, and a welcoming environment for international students.
Want to calculate your PhD admission chances? Try it here:
https://phdfinder.com/2026/03/12/phd-admission-chance-calculator/
We’re an independent team helping students find opportunities.
Found this opportunity helpful? Support us with a coffee!
