Project Assistant Post-Doc at the Institute of Building and Industrial Construction

Project Assistant Post-Doc 40 hours / week | limited to 2 years

The Center of Artificial Intelligence & Machine Learning (CAIML) research group at the Institute of Building and Industrial Construction, TU Wien, is seeking a Postdoctoral Researcher in Unsupervised Fault Detection and Diagnosis (FDD) for building and HVAC systems. The successful candidate will work on data-driven methods for detecting, diagnosing, and explaining faults in complex building systems using largescale sensor and operational data. The position focuses on unsupervised and explainable AI approaches, with the goal of delivering trustworthy and actionable diagnostics for real-world building operations. TU Wien is Austria's largest institution of research and higher education in the fields of technology and natural sciences. As a driver of innovation, TU Wien fosters close collaboration with business and industry and contributes to the prosperity of society.

Key responsibilities :

• Design and develop unsupervised and weakly supervised methods for fault detection and diagnosis in building and HVAC systems.
• Analyze large-scale, high-dimensional time-series data from building automation systems using machine learning techniques.
• Develop interpretable and explainable models to support root-cause analysis and actionable diagnostics.
• Contribute to peer-reviewed publications, open science outputs, and dissemination activities.

Your profile :

We welcome applicants from diverse academic backgrounds. This includes, but is not limited to : machine learning, data scientists, and engineers with an interest in empirical research.

Entry level salary is determined by the pay grade B1 of the Austrian collective agreement for project assistant. This is a minimum of currently EUR 5.540,50 / month gross, 14 times / year for 40 hours / week. Expected start : as soon as possible (latest March 2026).

TU Wien is committed to increasing the proportion of women in particular in leadership positions. Female applicants are explicitly encouraged to apply. People with special needs are equally encouraged to apply. In case of any questions, please contact the confidant for disabled persons at the university, Mr. Gerhard Neustätter.