AI & Machine Learning Training for the Raw Materials Sector

This Call seeks innovative, modular, and industry-relevant learning programmes that will empower professionals, enterprises, and public authorities to adopt digital technologies and drive the green and digital transitions across the raw and advanced materials value chain.

About the Call

As part of the EU’s strategic drive for a digitally skilled and sustainable workforce, this call supports the creation of a high-impact AI/ML training programme. The selected course will be integrated into course portfolio of the European Raw Materials Academy, and will be hosted via the EIT RawMaterials Skills Hub platform– Europe’s digital training marketplace for the raw materials industry. In addition to procurement funding for the development of this training programme, the results will be co-commercialised with EIT RawMaterials.

Training providers will have the opportunity to:

• Deliver a flagship course in Europe’s European Raw Materials Academy
• Access co-branding and revenue-sharing via the Skills Hub
• Collaborate with top-tier industry and academic partners

Objectives

The training programme will:

• Introduce foundational AI/ML concepts tailored to the raw materials industry
• Apply data science and machine learning tools to real-world materials industry challenges
• Support upskilling for professionals across technical, managerial, and operational roles and across the raw materials value chain
• Embed interactive, self-paced, SCORM-compliant content into the Skills Hub platform
• Comply with the EIT RawMaterials Quality Framework and align with EU workforce and education standards

Who Should Apply

We welcome applications from:

• Experienced training and digital learning providers
• Industry actors with AI/ML expertise
• Consortia involving at least one academic/research and one industrial partner
• Entities from across EU and Horizon Europe-associated countries

Applicants should demonstrate:

• Capability in modular eLearning course development
• Access to sector-relevant data, use cases, and technical experts
• Commitment to quality, scalability, and impact

What We’re Looking For

Industry-relevant solutions for AI/ML could include:

• Advanced and more reliable exploration models
• Optimized processes based on big data analysis and deep learning strategies (smart algorithms, exploration data analytics, Digital Twins, etc.)
• Enhanced safety and predictive solutions for monitoring and maintenance
• Integration of single elements of the value chain into a truly circular model

Example course topics:

• AI for Advanced and reliable exploration models and big data analysis
• LCA for mining processing and downstream (AM) and recycling
• Integrating various levels of Geo-science data (from nanoscale to macro and remote sensing level)
• Predictive AI for enhancing safety - across supply chain (extraction, processing, handling)
• Machine Learning techniques for identifying and managing risks
• Applicability of AI in Circular Economy Practices and Design
• AI for Resource efficiency

The course should be:

• Modular and SCORM-compliant for flexible online delivery
• Targeted to sector-specific applications
• Interactive, incorporating case studies, simulations, quizzes, and learner assessments
• Designed to issue micro-credentials and align with the EIT Quality Management Framework

Funding Details

• Target Budget: €60,000–€80,000
• Co-commercialisation: Revenue-sharing agreement for future course delivery
• Delivery Deadline: Q1 2026 (incl. pilot and QA testing)

How to Apply

Proposals must be emailed in English along with all accompanying documents to the following address:

Adnan Hardwarewala
adnan.hardwarewala@eitrawmaterials.eu

Timelines

• Deadline for Clarifications: 11 July 2025
• Submission Deadline: 18 July 2025, 13:00 CET

Contact

Questions? Reach out to:
adnan.hardwarewala@eitrawmaterials.eu

Important Documents

• Proposal template
• Financial offer (no template, please use preferred format)
• Tenderers’ declaration