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Master EXA Intelligence: AI and Advanced Modeling in Energy

The path of excellence that combines computational power, artificial intelligence and industrial innovation at the service of the energy sector.

Advanced master’s programme for new skills in the energy of the future

The Master’s in EXA Intelligence: AI and Advanced Modeling in Energy, created through a partnership between Eni and Cefriel, the digital innovation center of the Politecnico di Milano, is an advanced training programme where high-level education, technological expertise and industrial application converge to transform data, artificial intelligence (AI), and supercomputing into energy solutions.

The programme explores the latest developments in AI and advanced modelling, with the aim of combining mathematical-physical models and high-performance computing to address the most complex industrial challenges. You will undergo a comprehensive journey that combines technical skills with a strong focus on the ethical and responsible use of new technologies, while also developing the managerial and project-based capabilities needed to operate in advanced industrial environments. 

The Master’s is part of Eni’s technological ecosystem, where expertise and projects integrate with AI systems, advanced modelling and supercomputing. The name “Exa” is inspired by the exascale threshold of supercomputing — the power required to perform one quintillion mathematical operations per second — a threshold achieved through the combination of the HPC6 and HPC7 supercomputers installed at Eni's Green Data Center.

EXA Intelligence Master: call for applications, selection process and deadlines

The Master’s program lasts 12 months and is aimed at 15 graduates (or students who will graduate by December 2026) in STEM disciplines. It includes immediate employment under an Advanced Training and Research Apprenticeship Contract upon completion of the programme and attainment of the Master’s.

Read all the details below and apply by December 10, 2026.

How to apply for the EXA Intelligence Masters: AI and Advanced Modeling in Energy

Admission requirements

The Master’s class will consist of 15 apprentices selected by Eni.

Candidates who, by the deadline of the call for applications, meet the following requirements will be invited to participate in the selection:

Have obtained, or expect to obtain by 31 December 2026, a Master's degree with a final grade of 100/110 or above (or an equivalent international qualification) in:

  • Physics – LM-17;  

  • Information Technology – LM-18; 

  • Chemical Engineering – LM-22; 

  • Automation Engineering – LM-25; 

  • Electronic Engineering – LM-29 

  • Energy and Nuclear Engineering – LM-30; 

  • Management Engineering – LM-31; 

  • Computer Engineering – LM-32; 

  • Mechanical Engineering – LM-33;  

  • Environmental and Land Engineering – LM-35; 

  • Mathematics – LM-40; 

  • Statistics – LM-44;

  • Materials Engineering – LM-53 

  • Artificial Intelligence and Data Science – LM-91

Other requirements:

  • Not have  turned  29 years old by December 31st, 2026 .

  • Have an excellent knowledge of English. For international candidates, a good knowledge of Italian will be considered  preferential. 

To learn more about the requirements, please consult the call for applications at the end of this page.

The structure of the Master’s

The training programme adopts a learning-by-doing approach, and lasts 12 months, comprising 12 months divided into 6 months of in-person lectures (including hands-on sessions and labs) held at the “La Goccia” Campus of Politecnico di Milano. The programme may also make use of additional facilities of Politecnico di Milano, Cefriel, or other venues dedicated to the Master's educational and project activities. The remaining 6 months are dedicated to a project work at at Eni and its Companies. The programme is delivered entirely in English by university and company lecturers and is enriched through case studies, seminars led by Eni managers, and sessions with industry experts.

The course awards a total of 63 CFU/ECTS credits. The table below shows the programme's teaching schedule and details.

Courses - 43 credits

  • AI-assisted Python Programming

  • AI Models

  • Generative e Agentic AI

  • AI & HPC Infrastructure

  • Scientific Machine Learning

  • Optimization

  • Advanced AI Applications, Manage-ment & Governance 

  • Management Skills

Project Work -20 credits

 

Higher Education and Research Apprenticeship Contract

Selected participants will be offered  an offer of a Higher Education and Research Apprenticeship Contract, which will remain valid throughout  the  duration of the Master’s.  In addition, all participants will receive a gross monthly stipend of €1,500 for the duration of the training programme (12 months).

The enrolment fee at Cefriel-PoliMi is paid directly by Eni to the aforementioned institution.

Completing the course

Upon completing  the programme, participants will be awarded a Level 2 Master’s Degree in EXA Intelligence: AI and Advanced Modeling in Energy from Politecnico di Milano.

 

Who is it aimed at

Admission requirements

The Master’s class will consist of 15 apprentices selected by Eni.

Candidates who, by the deadline of the call for applications, meet the following requirements will be invited to participate in the selection:

Have obtained, or expect to obtain by 31 December 2026, a Master's degree with a final grade of 100/110 or above (or an equivalent international qualification) in:

  • Physics – LM-17;  

  • Information Technology – LM-18; 

  • Chemical Engineering – LM-22; 

  • Automation Engineering – LM-25; 

  • Electronic Engineering – LM-29 

  • Energy and Nuclear Engineering – LM-30; 

  • Management Engineering – LM-31; 

  • Computer Engineering – LM-32; 

  • Mechanical Engineering – LM-33;  

  • Environmental and Land Engineering – LM-35; 

  • Mathematics – LM-40; 

  • Statistics – LM-44;

  • Materials Engineering – LM-53 

  • Artificial Intelligence and Data Science – LM-91

Other requirements:

  • Not have  turned  29 years old by December 31st, 2026 .

  • Have an excellent knowledge of English. For international candidates, a good knowledge of Italian will be considered  preferential. 

To learn more about the requirements, please consult the call for applications at the end of this page.

Programme

The structure of the Master’s

The training programme adopts a learning-by-doing approach, and lasts 12 months, comprising 12 months divided into 6 months of in-person lectures (including hands-on sessions and labs) held at the “La Goccia” Campus of Politecnico di Milano. The programme may also make use of additional facilities of Politecnico di Milano, Cefriel, or other venues dedicated to the Master's educational and project activities. The remaining 6 months are dedicated to a project work at at Eni and its Companies. The programme is delivered entirely in English by university and company lecturers and is enriched through case studies, seminars led by Eni managers, and sessions with industry experts.

The course awards a total of 63 CFU/ECTS credits. The table below shows the programme's teaching schedule and details.

Courses - 43 credits

  • AI-assisted Python Programming

  • AI Models

  • Generative e Agentic AI

  • AI & HPC Infrastructure

  • Scientific Machine Learning

  • Optimization

  • Advanced AI Applications, Manage-ment & Governance 

  • Management Skills

Project Work -20 credits

 

Higher Education and Research Apprenticeship Contract

Higher Education and Research Apprenticeship Contract

Selected participants will be offered  an offer of a Higher Education and Research Apprenticeship Contract, which will remain valid throughout  the  duration of the Master’s.  In addition, all participants will receive a gross monthly stipend of €1,500 for the duration of the training programme (12 months).

The enrolment fee at Cefriel-PoliMi is paid directly by Eni to the aforementioned institution.

Qualification

Completing the course

Upon completing  the programme, participants will be awarded a Level 2 Master’s Degree in EXA Intelligence: AI and Advanced Modeling in Energy from Politecnico di Milano.

 

Documents

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