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The BOOSTalent Project brings together an eight-partner consortium, comprised of five HEIs and three business partners, to enhance institutional innovation and entrepreneurship practices. With a vision for 2030, the consortium aims to foster innovation in AI and machine learning (ML) across HEIs, students, and businesses, particularly in the fields of aerospace, electronics, advanced materials, sustainability, and biodiversity.

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Fundamentals of materials joining and processing

Fundamentals of materials science

Tools of Machine Learning

Density functional theory for computational materials design

Introduction to Powder Technologies

Advanced Powder Technologies

Machine Learning in Materials Lifecycle

Mathematical Foundations of Machine Learning

Fundamentals of phase transformations in metals and alloys

Methods for studying structure and properties of steels and alloys

Advanced powder technologies

Fundamentals of deformation and fracture of materials and structures

Supervised Machine Learning

Unsupervised Machine Learning

MACHINE LEARNING IN ATOMISTIC MATERIALS SCIENCE

Ab initio calculations of electronic properties of materials with Quantum ESPRESSO package

Manifold Learning

ADVANCED CERAMIC NANOCOMPOSITES

Digital twins for advanced materials and sustainable structures

From first principles to machine learning methods in materials informatics

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