Master Thesis “AI-Based Condition Monitoring for Autonomous Mobile Work Machines”

AIT Austrian Institute of Technology

As Austria's largest research and technology organisation for applied research, we are dedicated to make substantial contributions to solving the major challenges of our time, climate change and digitalisation. To achieve our goals, we rely on our specific research, development and technology competencies, which are the basis of our commitment to excellence in all areas. With our open culture of innovation and our motivated, international teams, we are working to position AIT as Austria's leading research institution at the highest international level and to make a positive contribution to the economy and society.

Our Center for Vision, Automation & Control (VAC) located in Vienna invites applications for a master’s thesis position. VAC exploits the opportunities of automation and digitalisation to develop intelligent solutions in computer vision, robotics and control. We work closely with industrial and academic partners to bring cutting-edge algorithms onto real machines and into real environments.

As part of the Competence Unit Assistive & Autonomous Systems (AAS), we research safe and dependable autonomous systems and mobile work machines for challenging outdoor and industrial scenarios. We focus on robust perception, localisation, planning and monitoring technologies that enable machines to operate reliably, reduce workload for human operators and increase overall system safety.

Master Thesis “AI-Based Condition Monitoring for Autonomous Mobile Work Machines”

Your tasks:

• Dive into the state of the art in vibration- and acoustic-based condition monitoring, anomaly and event detection, and identify promising methods.
• Prototype on established open datasets, implementing and benchmarking AI-based anomaly and event detection methods (e.g., feature-based models, one-class approaches, autoencoders, lightweight CNNs) using vibration and/or machine-sound data.
• Design a compact sensor concept for a real work machine, selecting suitable vibration and/or audio sensors and defining mounting positions on or near the critical mechanical structures.
• Support data acquisition on a test platform or test rig, recording and labelling normal operation under different loads and operating modes, as well as selected anomaly scenarios (e.g., imbalance, loosened non-critical components, controlled impact / foreign-object events).
• Develop end-to-end detection pipelines, from signal preprocessing (filtering, feature extraction, time-frequency representations) to model training and thresholding for online anomaly and event detection.
• Systematically evaluate and compare your models, analysing detection rates, false alarms, and robustness to operating conditions and noise, and assessing the impact of different sensor configurations (vibration vs. audio vs. sensor fusion) and model choices.
• Work as part of an experienced research team, receive close mentorship from scientists in robotics, machine learning and control, and learn how to plan, document and present an applied research project in a professional R&D environment – giving your scientific career a strong, application-driven kick-start.

Your qualifications:

• Ongoing master’s studies in Robotics, Automation, Mechatronics, Electrical Engineering, Computer Science, Data Science or a related technical field.
• Solid programming skills in Python; experience with scientific libraries (e.g., NumPy, SciPy, Pandas) is expected, first experience with machine learning frameworks (e.g., PyTorch, TensorFlow, scikit-learn) is an advantage.
• Basic knowledge of signal processing and machine learning, or strong motivation to build up these skills quickly.
  Strong interest in autonomous systems, mobile work machines, sensing and embedded AI.
• Hands-on mindset and willingness to work with real hardware, experimental setups and sensor data.
• Ability to work both independently and as part of a team, as well as good command of English (spoken and written).

What to expect:

• Duration of the master’s thesis: 6 months.
• Start date: ideally, as soon as possible
• The opportunity to kick-start your scientific career in an applied research environment, work with modern labs and real autonomous mobile work machines.
• EUR 1.005,06 gross per month for 20 hours/week based on the collective agreement. There will be additional company benefits. As a research institution, we are familiar with the supervision and execution of master theses, and we are looking forward to supporting you accordingly!

At AIT, we create an inclusive and family-friendly working environment that promotes equal opportunities and actively strengthens diversity across our workforce and in leadership positions. Among other initiatives, we are committed to increasing the proportion of women in our company and therefore particularly welcome applications from female applicants.

TOMORROW TODAY - WITH YOU?

Please submit your complete application documents online, consisting of your CV, a cover letter, relevant certificates and documents, as well as a proof of identity: https://jobs.ait.ac.at/Job/262557