PhD Position in Graph-based Machine Learning Methods for Predictive Maintenance
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PhD Position in Graph-based Machine Learning Methods for Predictive Maintenance
Applicants are invited for a PhD fellowship/scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Electrical and Computer Engineering programme. The position is available from 01 May 2026 or later. You can submit your application via the link under 'how to apply'.
Title:
PhD Position in Graph-based Machine Learning Methods for Predictive Maintenance
Research area and project description:
Unplanned machine failures cause costly downtime in industrial production. Predictive maintenance aims to prevent this by learning from sensor data to detect early signs of failure, but existing approaches often struggle due to the rarity of failure events and the evolving behavior of industrial machines.
Industrial machines are complex systems composed of interacting components, where sensor signals are inherently linked through physical and functional relationships. This PhD project, funded by the Independent Research Fund Denmark (DFF), focuses on developing innovative AI-based methods for the predictive maintenance of industrial machines. By bridging Graph Machine Learning with Signal Processing, the project moves beyond fully data-driven methods to explicitly model these physical interactions and the time-dependent nature of sensor signals. A core focus is overcoming the small-data challenge by developing robust models that remain accurate even when failure events are rare and historical data is limited.
The developed methods will be evaluated on multiple datasets, including public benchmarks and proprietary sensor data from Danish industry, to enable earlier and more reliable failure prediction in practical applications.
We seek a motivated candidate with:
Place of employment and place of work:
The place of employment is Aarhus University, and the place of work is Department of Electrical and Computer Engineering, Katrinebjerg, Finlandsgade 22, 8200 Aarhus N, Denmark.
Contacts:
Applicants seeking further information regarding the PhD position are invited to contact:
How to apply:
Please follow this link to submit your application.
Application deadline is 15 February 2026 at 23:59 CET.
Preferred starting date is 1 May 2026.
Please note:
Title:
PhD Position in Graph-based Machine Learning Methods for Predictive Maintenance
Research area and project description:
Unplanned machine failures cause costly downtime in industrial production. Predictive maintenance aims to prevent this by learning from sensor data to detect early signs of failure, but existing approaches often struggle due to the rarity of failure events and the evolving behavior of industrial machines.
Industrial machines are complex systems composed of interacting components, where sensor signals are inherently linked through physical and functional relationships. This PhD project, funded by the Independent Research Fund Denmark (DFF), focuses on developing innovative AI-based methods for the predictive maintenance of industrial machines. By bridging Graph Machine Learning with Signal Processing, the project moves beyond fully data-driven methods to explicitly model these physical interactions and the time-dependent nature of sensor signals. A core focus is overcoming the small-data challenge by developing robust models that remain accurate even when failure events are rare and historical data is limited.
The developed methods will be evaluated on multiple datasets, including public benchmarks and proprietary sensor data from Danish industry, to enable earlier and more reliable failure prediction in practical applications.
- Project description. For technical reasons, you must upload a project description. Please simply copy the project description above and upload it as a PDF in the application.
We seek a motivated candidate with:
- A Master’s degree (equivalent to 120 ECTS) in Electrical and Computer Engineering, Computer Science, Data Science, Applied Mathematics, or a closely related discipline. Candidates expected to complete their MSc by July 2026 can also apply.
- A strong background and demonstrated aptitude in machine learning, signal processing, mathematics, and computer programming.
- A genuine enthusiasm for research, particularly in algorithm design, and a collaborative mindset.
Place of employment and place of work:
The place of employment is Aarhus University, and the place of work is Department of Electrical and Computer Engineering, Katrinebjerg, Finlandsgade 22, 8200 Aarhus N, Denmark.
Contacts:
Applicants seeking further information regarding the PhD position are invited to contact:
- Associate Professor Naveed ur Rehman, naveed.rehman@ece.au.dk (main supervisor)
How to apply:
Please follow this link to submit your application.
Application deadline is 15 February 2026 at 23:59 CET.
Preferred starting date is 1 May 2026.
Please note:
- Only documents received prior to the application deadline will be evaluated. Thus, documents sent after deadline will not be taken into account.
- The programme committee may request further information or invite the applicant to attend an interview.
- Shortlisting will be used, which means that the evaluation committee only will evaluate the most relevant applications.