Project title: AI in predictive maintenance of complex technical systems

Description:
Step into the future of autonomous public transport with our innovative internship program at the Cyber-Physical Systems Laboratory. As driverless technologies advance and get incorporated into the transportation infrastructure, ensuring the reliability of these vehicles is crucial. This project leverages artificial intelligence (AI), Digital Twin technologies, and Predictive Maintenance to monitor and maintain the health state of complex technical systems. The system of focus will be autonomous trains.
As an intern, you will work in the Cyber-Physical Systems Laboratory of the Center for Digital Engineering on:
➔ Analyzing data from autonomous train sensors.
➔ Developing AI-driven predictive maintenance models.
➔ Integrating AI tools into the predictive maintenance system.
This hands-on experience will deepen your understanding of AI applications in engineering and transportation. Ideal candidates should have a background in data analysis, machine learning, or engineering, with a keen interest in autonomous vehicles and predictive maintenance.
Join us to contribute to the reliability and efficiency of autonomous public transport, driving innovation in the field.

Candidates requirements:
➔ Python programming skills
➔ Experience with machine learning and neural networks

English language proficiency is not required.

Supervisor: Professor of the Practice Andreas Panayi & Project Manager Tikhon Uglov

Internship duration: 1-2 months

The start date of the internship: now, latest start date March 31, 2025

Monthly compensation: With No compensation

Contact person: Andreas Panayi a.panayi@skoltech.ru

Description of the internship in Russian