Master's in AI for Engineering in Salamanca 2026: 60 ECTS and Career Opportunities

Key data

Technical professionals, engineers and companies in the industrial sector have had since October 2026 a new official postgraduate training pathway in artificial intelligence. The University of Salamanca has formalized through a rectoral resolution the curriculum of the Master's Degree in Data Science and Artificial Intelligence Applied to Engineering, published in the BOE on October 19, 2026 with reference BOE-A-2026-21779.

The degree has official status following the Council of Ministers Agreement of September 15, 2026, which guarantees its recognition for academic and professional purposes throughout the State.

What does this regulation establish?

The resolution publishes the complete curriculum of the new master's program, structured in 60 ECTS distributed across three distinct blocks:

The program falls within the field of Computer Science and Systems Engineering, which distinguishes it from other AI master's programs with a more generalist or pure science profile. The approach is explicitly applied to the industrial and engineering environment.

The sectoral electives allow students to specialize their profile in four specific areas:

• Energy optimization: application of AI to the management and efficiency of energy systems.
• Food traceability: use of data and AI in supply chains of the agri-food sector.
• Civil infrastructure: predictive models and data analysis applied to civil engineering and construction.
• Satellite imagery: processing and interpretation of remote sensing data with AI techniques.

Economic and operational impact

For companies, the emergence of this official degree has immediate practical consequences in three areas:

Access to specialized talent. Industrial, energy, agri-food and civil engineering companies now have a regulated and recognized training profile to fill positions such as data analyst, AI engineer or intelligent automation specialist. Until now, many of these profiles were filled with graduates from heterogeneous training backgrounds or without specific official qualifications.

Selection criteria and salary valuation. As an official degree with 60 ECTS, it can be used as an objective criterion in internal calls, public competitions and collective bargaining negotiations. This is especially relevant for companies with contracts with the Administration or participating in tenders that require accreditation of AI capabilities.

Continuous training of staff. Active technical professionals (industrial, telecommunications, civil or computer engineers) can access this master's program to upskill. Companies that finance or co-finance this training can benefit from available subsidized training credits through the professional training for employment system.

Who does it affect?

• Engineering graduates (industrial, computer science, civil, telecommunications, agricultural) seeking specialization in AI and data.
• Active technical professionals who need to accredit competencies in Machine Learning, Deep Learning or Generative AI.
• Energy sector companies interested in specialized profiles in energy optimization with AI.
• Agri-food industry requiring experts in traceability and supply chain data analysis.
• Infrastructure and civil engineering companies applying predictive models or structural data analysis.
• HR and recruitment departments that must evaluate candidates with training in AI applied to engineering.
• R&D departments of industrial companies seeking to incorporate AI capabilities in their processes.
• The University of Salamanca itself, which expands its official postgraduate offering in emerging technologies.

Practical example

An energy sector company with a team of engineers managing electrical distribution networks needs to incorporate demand prediction and anomaly detection capabilities through AI. Until now, none of its technicians had official training in these subjects.

With the entry into force of this master's program, the company can:

1. Identify one or two engineers with appropriate technical profile and finance their enrollment in the master's program (60 ECTS, completable in one academic year full-time).
2. Direct the choice of electives towards the energy optimization specialty (12 ECTS), directly aligned with its activity.
3. Propose the Master's Final Project (12 ECTS) as a project applied to a real company challenge, thus obtaining a deliverable with immediate operational value.
4. Accredit to clients, auditors or public bidders that it has personnel with official qualifications in AI applied to engineering.

This scheme is replicable in the civil infrastructure, agri-food and satellite remote sensing sectors, adapting the corresponding elective.

What should companies do now?

1. Identify AI talent needs: review what positions or internal projects require competencies in Machine Learning, Deep Learning or Generative AI applied to engineering processes.
2. Evaluate existing staff upskilling: identify engineers or technicians with appropriate profile to take the master's program and assess co-financing through subsidized training credits.
3. Update selection profiles: include this official degree as an evaluation criterion in job postings for advanced analytics, automation or R&D positions.
4. Explore collaboration with the University of Salamanca: contact the institution to assess internship agreements, applied master's project agreements or applied research partnerships.
5. Review public tenders and contracts: if the company operates with the Administration in sectors such as energy, infrastructure or food, verify whether AI accreditation is or will be a requirement in upcoming calls.

Official source

Consult complete regulation in official source

Notice: This article is for informational purposes only and does not constitute legal advice. For specific decisions, consult a qualified professional. Source: https://www.boe.es/diario_boe/txt.php?id=BOE-A-2026-21779