PhD Position in Graph-based Machine Learning Methods for Predictive Maintenance

Role Summary

• PhD fellowship/scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark
• Within the Electrical and Computer Engineering programme
• Position available from 1 May 2026 or later
• Application deadline: 15 February 2026 at 23:59 CET

Research Area and Project Description

• Focus on predictive maintenance to prevent costly unplanned machine failures in industrial production
• Project funded by the Independent Research Fund Denmark (DFF)
• Develop AI-based methods combining Graph Machine Learning and Signal Processing
• Explicitly model physical interactions and time-dependent sensor signals
• Address small-data challenge: robust models for rare failure events and limited historical data
• Methods evaluated on public benchmarks and proprietary Danish industry sensor data
• Aim: enable earlier and more reliable failure prediction in practical applications

Responsibilities

• Conduct research on graph-based machine learning for predictive maintenance
• Develop and evaluate new AI methods
• Collaborate with academic and industry partners

Requirements

• Master’s degree (120 ECTS) in Electrical and Computer Engineering, Computer Science, Data Science, Applied Mathematics, or related discipline
• Candidates completing MSc by July 2026 are eligible
• Strong background in machine learning, signal processing, mathematics, and computer programming
• Enthusiasm for research, especially algorithm design
• Collaborative mindset

Place of Employment

• Aarhus University
• Department of Electrical and Computer Engineering, Katrinebjerg, Finlandsgade 22, 8200 Aarhus N, Denmark

Contacts

• Main supervisor: Associate Professor Naveed ur Rehman ([email protected])
• For application requirements: [email protected]

How to Apply

• Submit your application via this link
• For application requirements and mandatory attachments, see the application guide
• Only documents received before the deadline will be evaluated
• Shortlisting will be used; only the most relevant applications will be evaluated
• The committee may request further information or invite for interview

Additional Information

• Aarhus University values equality and diversity; all candidates are encouraged to apply
• Salary and terms of employment follow the applicable collective agreement
• Please mention in your application that you found the job at Jobindex