PhD Position in Hierarchical Graph Neural Networks for Multi-Scale Urban Energy Systems 100%
Empa, Materials Science and Technology
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"As Switzerland's incubator for innovation, Empa's research provides answers to the most pressing challenges facing
industry." Prof. Dr. Katharina Maniura, Biointerfaces "Empa's research on the highest international level plays a
leading role in the advancement of technology." Prof. Dr. Ayodhya Nath Tiwari, Thin Films and Photovoltaics "Empa's
materials science and technology research is of great benefit to society in the fields of energy, mobility,
environment, construction and health." Prof. Dr. Bernd Nowack, Technology and Society "For my research projects I use
first-class equipment. This is extremely important in dynamic 3D radiography." Dr. Ameet Aiyangar, Mechanical Systems
Engineering "Empa offers good employment conditions and supports equal opportunities. I consider this very important."
Irene Ferretto, Advanced Materials Processing "Empa has sites in three attractive regions in Switzerland. This also
ensures a good quality of life." Dr. Shanyu Zhao, Building Energy Materials and Components "We enjoy working in a team.
For us it is important that Empa pursues topics like sustainability and innovation." Michael Levy and Nikola Tatalovic,
Finances/Controlling "My work is exciting and highly diverse - and I am right there when research projects are being
implemented in NEST, Empa's research and innovation building." Yannic Trüb, Real Estate Management "At Empa I value the
good work environment and international collaboration." Subas Scheibler, Particles-Biology Interactions
PhD Position in Hierarchical Graph Neural Networks for Multi-Scale Urban Energy Systems
Share Apply now Materials science and technology are our passion. With our cutting-edge research, Empa's around 1,100
employees make essential contributions to the well-being of society for a future worth living. Empa is a research
institution of the ETH Domain.The Urban Energy Systems Laboratory (UESL) pioneers strategies, solutions, and methods to
support the development of sustainable, resilient, and equitable urban energy systems. Our work combines technology and
policy with systems thinking and practical implementation, always grounded in real-world urban challenges.
This PhD position is offered in collaboration with the Intelligent Maintenance and Operations Systems (IMOS)
Laboratory at EPFL (Prof. Olga Fink). IMOS focuses on the development of intelligent algorithms designed to improve the
performance, reliability, and availability of complex industrial systems while making maintenance strategies more
cost-efficient.
Together, UESL and IMOS are seeking a motivated and qualified PhD candidate to advance the use of hierarchical graph
neural networks for modeling multi-scale urban energy systems. By combining advances in Physics-Informed Machine
Learning (PIML) and Graph Neural Networks (GNNs) with real-world energy applications, the project aims to better
capture the dynamics of urban infrastructures across different spatial and temporal scales, from building-level energy
demand to district-scale interactions and their integration with wider energy networks.
Your tasks
The focus of this research is to design and develop (physics-informed) hierarchical graph neural network architectures
that can capture the complexity of multi-scale urban energy infrastructures. The PhD will explore how these models can
represent spatial and temporal dependencies in systems, such as building energy demand, district heating and cooling,
storage, and local electricity grids. A key goal is to translate methodological innovations in deep learning into
practical tools for sustainable urban energy systems, supporting applications in forecasting, system optimization,
flexibility management, and resilience analysis. The work will be carried out in close collaboration with our
interdisciplinary teams at both Empa and EPFL, as well as external academic and industry partners.
Your profile
You are a highly motivated and talented candidate with a Master’s degree in Engineering, Control, Computer Science,
Physics, Applied Mathematics, or a related field. You bring a strong analytical background and are proficient in areas
like geometric deep learning, signal processing, statistics, or learning theory. Knowledge of energy systems,
multi-energy infrastructures, or urban energy applications is a strong asset. You are self-driven, creative, and bring
strong problem-solving skills as well as the ability to work in an interdisciplinary environment. Proficiency in
English (spoken and written) is required; good comprehension and oral skills in German are desirable.
Our offer
We offer a multifaceted and challenging PhD position in a modern research environment with excellent infrastructure.
The candidate will benefit from joint supervision by Prof. Olga Fink (EPFL IMOS) and the UESL team at Empa, combining
cutting-edge expertise in machine learning and energy system modeling with strong ties to academic and industry
partners. The PhD is intended to be formally enrolled at EPFL. The ideal starting date is January 2026, or upon mutual
agreement.We live a culture of inclusion and respect. We welcome all people who are interested in innovative,
sustainable and meaningful activities - that's what counts.We look forward to receiving your complete online
application including a letter of motivation, an up-to-date CV, transcripts of all obtained degrees (in English), a
brief research statement (one page) describing your project idea in the field of physics-informed deep learning
algorithms, one publication (e.g. MSc thesis or preferably a conference/journal publication, link is sufficient).
Please submit these exclusively via our job portal. Applications by e-mail and by post will not be
considered.PatriciaNitzsche, Stv. Leiterin Human Resources / Dep. Head Human Resources
Questions?
DrGeorgiosMavromatidis
Head of Laboratory
Urban Energy Systems
https://uesl.empa.ch
Your future place of work
Empa
Ueberlandstrasse 129
8600Dübendorf
Empa as an employer
Innovative, sustainable, meaningful activities Creating added value for society International, multicultural working
environment Freedom to create and develop Culture of inclusion and respect Excellent balance between different areas of
life Multiple award-winning and certified employer Benefits for rail, mobile, childcare, catering, etc.
Good to know
Empa website
Working in Switzerland
Employment process
Conditions of employment
Apply now
industry." Prof. Dr. Katharina Maniura, Biointerfaces "Empa's research on the highest international level plays a
leading role in the advancement of technology." Prof. Dr. Ayodhya Nath Tiwari, Thin Films and Photovoltaics "Empa's
materials science and technology research is of great benefit to society in the fields of energy, mobility,
environment, construction and health." Prof. Dr. Bernd Nowack, Technology and Society "For my research projects I use
first-class equipment. This is extremely important in dynamic 3D radiography." Dr. Ameet Aiyangar, Mechanical Systems
Engineering "Empa offers good employment conditions and supports equal opportunities. I consider this very important."
Irene Ferretto, Advanced Materials Processing "Empa has sites in three attractive regions in Switzerland. This also
ensures a good quality of life." Dr. Shanyu Zhao, Building Energy Materials and Components "We enjoy working in a team.
For us it is important that Empa pursues topics like sustainability and innovation." Michael Levy and Nikola Tatalovic,
Finances/Controlling "My work is exciting and highly diverse - and I am right there when research projects are being
implemented in NEST, Empa's research and innovation building." Yannic Trüb, Real Estate Management "At Empa I value the
good work environment and international collaboration." Subas Scheibler, Particles-Biology Interactions
PhD Position in Hierarchical Graph Neural Networks for Multi-Scale Urban Energy Systems
Share Apply now Materials science and technology are our passion. With our cutting-edge research, Empa's around 1,100
employees make essential contributions to the well-being of society for a future worth living. Empa is a research
institution of the ETH Domain.The Urban Energy Systems Laboratory (UESL) pioneers strategies, solutions, and methods to
support the development of sustainable, resilient, and equitable urban energy systems. Our work combines technology and
policy with systems thinking and practical implementation, always grounded in real-world urban challenges.
This PhD position is offered in collaboration with the Intelligent Maintenance and Operations Systems (IMOS)
Laboratory at EPFL (Prof. Olga Fink). IMOS focuses on the development of intelligent algorithms designed to improve the
performance, reliability, and availability of complex industrial systems while making maintenance strategies more
cost-efficient.
Together, UESL and IMOS are seeking a motivated and qualified PhD candidate to advance the use of hierarchical graph
neural networks for modeling multi-scale urban energy systems. By combining advances in Physics-Informed Machine
Learning (PIML) and Graph Neural Networks (GNNs) with real-world energy applications, the project aims to better
capture the dynamics of urban infrastructures across different spatial and temporal scales, from building-level energy
demand to district-scale interactions and their integration with wider energy networks.
Your tasks
The focus of this research is to design and develop (physics-informed) hierarchical graph neural network architectures
that can capture the complexity of multi-scale urban energy infrastructures. The PhD will explore how these models can
represent spatial and temporal dependencies in systems, such as building energy demand, district heating and cooling,
storage, and local electricity grids. A key goal is to translate methodological innovations in deep learning into
practical tools for sustainable urban energy systems, supporting applications in forecasting, system optimization,
flexibility management, and resilience analysis. The work will be carried out in close collaboration with our
interdisciplinary teams at both Empa and EPFL, as well as external academic and industry partners.
Your profile
You are a highly motivated and talented candidate with a Master’s degree in Engineering, Control, Computer Science,
Physics, Applied Mathematics, or a related field. You bring a strong analytical background and are proficient in areas
like geometric deep learning, signal processing, statistics, or learning theory. Knowledge of energy systems,
multi-energy infrastructures, or urban energy applications is a strong asset. You are self-driven, creative, and bring
strong problem-solving skills as well as the ability to work in an interdisciplinary environment. Proficiency in
English (spoken and written) is required; good comprehension and oral skills in German are desirable.
Our offer
We offer a multifaceted and challenging PhD position in a modern research environment with excellent infrastructure.
The candidate will benefit from joint supervision by Prof. Olga Fink (EPFL IMOS) and the UESL team at Empa, combining
cutting-edge expertise in machine learning and energy system modeling with strong ties to academic and industry
partners. The PhD is intended to be formally enrolled at EPFL. The ideal starting date is January 2026, or upon mutual
agreement.We live a culture of inclusion and respect. We welcome all people who are interested in innovative,
sustainable and meaningful activities - that's what counts.We look forward to receiving your complete online
application including a letter of motivation, an up-to-date CV, transcripts of all obtained degrees (in English), a
brief research statement (one page) describing your project idea in the field of physics-informed deep learning
algorithms, one publication (e.g. MSc thesis or preferably a conference/journal publication, link is sufficient).
Please submit these exclusively via our job portal. Applications by e-mail and by post will not be
considered.PatriciaNitzsche, Stv. Leiterin Human Resources / Dep. Head Human Resources
Questions?
DrGeorgiosMavromatidis
Head of Laboratory
Urban Energy Systems
https://uesl.empa.ch
Your future place of work
Empa
Ueberlandstrasse 129
8600Dübendorf
Empa as an employer
Innovative, sustainable, meaningful activities Creating added value for society International, multicultural working
environment Freedom to create and develop Culture of inclusion and respect Excellent balance between different areas of
life Multiple award-winning and certified employer Benefits for rail, mobile, childcare, catering, etc.
Good to know
Empa website
Working in Switzerland
Employment process
Conditions of employment
Apply now