PhD Position within EU-MSCA project RESTORATIVE

Organisation/Company Politecnico di Milano Department Dipartimento di Energia Research Field Engineering » Industrial engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 30 Jun 2026 - 23:59 (Europe/Rome) Country Italy Type of Contract Temporary Job Status Full-time Hours Per Week 40 Offer Starting Date 1 Nov 2026 Is the job funded through the EU Research Framework Programme? Horizon Europe - MSCA Marie Curie Grant Agreement Number Is the Job related to staff position within a Research Infrastructure? No

Offer Description

Title: Development of Generative AI Models for Intelligent Maintenance of Thermomechanical Energy Storage Systems

Context: The proposed PhD falls within the project “Grid-scale Energy Storage: Imperatives for Accelerating the Green Transition (RESTORATIVE)” funded by the European Union’s Horizon Europe’s Research and innovation Programme under the Marie Skłodowska-Curie Grant Agreement No. . RESTORATIVE aims to develop technology for accelerating the green transition through Thermo-Mechanical Grid-Scale Energy Storage Systems (TM-GSES).

Project Home: The candidate will join the Laboratory of Analysis of Systems for the Assessment of Reliability, Risk and Resilience (LASAR3) at Politecnico di Milano and conduct research under the supervision of Professors Piero Baraldi and Enrico Zio.

Collaborative Environment: Within the RESTORATIVE project, the PhD researcher will collaborate with a multidisciplinary team of 17 doctoral fellows from institutions across Europe to bridge technological and policy gaps in the energy sector.

About the PhD Research: The industrial success of TM-GES will depend on their functional reliability to continuously provide stability and flexibility to the grid. To achieve this, methods are needed for the accurate prediction of degradation to inform intelligent maintenance strategies. Artificial Intelligence (AI) can be employed for this, but it requires extensive field data which are unavailable for new‑design systems such as TM-GES. In this context, the objective of the PhD research is to develop Generative Artificial Intelligence methods to predict the degradation state of key TM‑GES components; the prediction outcomes will eventually be integrated within an optimisation framework for intelligent maintenance.

Key Responsibilities

• Research & Development: develop AI methods to predict component degradation and optimisation models to plan intelligent maintenance.
• Collaboration: work closely with other project partners to deploy the developed methods to TM‑GES systems.
• Secondments: to be defined strategically for the benefit of a successful PhD and project.

Training

Participate in the project network‑wide PhD training schools covering technical topics such as thermodynamics, entrepreneurship, and reliability engineering.

Requirements

• Educational Background: completed Master’s degree in Engineering, Mathematics, Physics or related disciplines.
• MSCA Eligibility: at the date of recruitment, the candidate must not already possess a doctoral degree.
• Mobility Rule: the candidate must not have resided or carried out main activity in Italy for more than 12 months in the 36 months immediately prior to recruitment.
• Skills: strong interest in energy systems, AI/Machine Learning, optimisation and decision‑making.

Compensation & Benefits

Competitive Salary: A gross annual salary of approximately €54,378.36 (pre‑tax and social security), including living and mobility allowances according to MSCA rules; an additional family allowance will be added if applicable. The period of employment is 3 years.

Career Development: Access to a personalized Career Development Plan and a vast international research network.