Title of Research
Artificial intelligence methods for reliability prediction and predictive maintenance
Description of the Research
Predicting the reliability and performing predictive maintenance is fundamental for enhancing the safety and profitability of complex industrial systems. The objective of the research program is to develop methods for reliability prediction and predictive maintenance. Specifically, the research will focus on the development of adaptive and explainable AI models, transfer learning methods and physics informed neural networks. One key issue for the application of AI is the estimation of the uncertainty of the predictions. To this aim, Bayesian Neural Networks, Monte Carlo dropout and other techniques will be also considered. The research will be done within the activities of PE1 FAIR Spoke 4: ADAPTIVE AI – Future Artificial Intelligence Research – CUP D53C22002380006
RESEARCH SCIENTIFIC SUPERVISORS
Prof. Piero Baraldi and Prof. Enrico Zio
PRESUMED DATE FOR STARTING ACTIVITIES
16/06/2023
ACTIVITIES THAT THE EARLY RESEARCHER WILL CARRY OUT
The research will be carried out within international collaborative projects with industries, research centers and universities. The research team will be formed by the supervisors, the research fellow and PhD and master thesis students. Periodic discussion meetings will be held to update the supervisors about the work carried out and the corresponding results, and to establish the next activities. The development of the program will take place at the laboratory Lasar (www.lasar.polimi.it) at the Department of Energy, Bovisa campus.
LINK FOR THE APPLICATION:
https://lnkd.in/dEUgfbn8
DEADLINE FOR THE APPLICATION:
May 22nd, 2023
ONLINE APPLICATION SYSTEM:
Online Services of Politecnico di Milano – section Open competitions and selections – Open competition/selection for allocation of job/post – Calls for temporary research fellowships (see the attached step-by-step guidance)
ANNUAL SALARY:
Euro 28500, gross of fees charged to the contractor (It is expected to amount to approximately 2100 euros per month, after taxes)
DURATION OF THE GRANT:
2 years
