TRUSTWORTHY ARTIFICIAL INTELLIGENCE FOR PREDICTIVE MAINTENANCE OF INDUSTRIAL EQUIPMENT
The increased availability of data from industrial equipment and the grown ability to treat these data by artificial intelligence (AI) methods have opened the doors for the development and application of predictive maintenance in several industrial sectors, like nuclear, oil and gas, energy, electronics and transportation. Practical implementation of predictive maintenance entails trustworthiness of the AI model outcomes.
The PhD position, available in Laboratory of Analysis of Systems for the Assessment of Reliability, Risk and Resilience (LASAR3), aims at developing new AI analytics for predictive maintenance based on the powerful emerging techniques of Deep and Transfer Learning, Physics-Informed Neural Networks and Generative Adversarial Networks for improving prediction accuracy, especially in case of imbalanced data, i.e. dew degradation and failure data (challenge i); Deep Ensembles and Bayesian Neural Networks for treating the uncertainty in AI models (challenge ii) and eXplainable Artificial Intelligence.
Call description: https://www.dottorato.polimi.it/fileadmin/user_upload/bandi/ciclo40/bandi_aggiuntivi/3_ott24/SCHEDA_4670-STEN-TRUSTWORTHY_ARTIFICIAL_INTELLIGENCE.PDF
Additional information: https://www.dottorato.polimi.it/fileadmin/user_upload/bandi/ciclo40/bandi_aggiuntivi/3_ott24/4670_4102_APPLICATION_STEN__TRUSTWORTHY_ARTIFICIAL_INTELLIGENCE_FOR_PREDICTIVE_MA.pdf
(alternatively, you can go to https://www.dottorato.polimi.it/en/prospective-phd-candidates/calls-and-regulations/40-cycle/3rd-additional-call-2024-25 and scroll at the bottom of the page to find the call entitled “TRUSTWORTHY ARTIFICIAL INTELLIGENCE FOR PREDICTIVE MAINTENANCE OF INDUSTRIAL EQUIPMENT”)
Grant starting date: 13/12/2024
Deadline for admission to the Call: 25/11/2024 14:00 PM (Italian Time C.E.T.)