MSCA programme in HE

Marie Skłodowska-Curie Actions

The Marie Skłodowska-Curie Actions fund excellent research and innovation and equip researchers at all stages of their career with new knowledge and skills, through mobility across borders and exposure to different sectors and disciplines. The MSCA help build Europe’s capacity for research and innovation by investing in the long-term careers of excellent researchers.

The MSCA also fund the development of excellent doctoral and postdoctoral training programmes and collaborative research projects worldwide. By doing so, they achieve a structuring impact on higher education institutions, research centres and non-academic organisations.

The MSCA promote excellence and set standards for high-quality researcher education and training in line with the European Charter for Researchers and the Code of Conduct for the recruitment of researchers.

There are 5 types of MSCA targeting different objectives.

  • Doctoral Networks (DN)
    Supporting programmes to train doctoral candidates in academic and non-academic organisations.
  • Postdoctoral Fellowships (PF)
    Supporting career perspectives and excellence of postdoctoral researchers.
  • Staff Exchanges (SE)
    Encouraging collaborations between organisations through staff exchanges.
  • COFUND
    Co-funding of regional, national and international programmes.
  • MSCA and Citizens
    Bringing research and researchers closer to the public at large.

More information on the Marie Skłodowska-Curie Actions is available here.

MSCA Doctoral Networks (DN) Projects

CINEMA - Chemistry informed machine learning in emulsion polymerization processes and products

Specific programme: HORIZON TMA MSCA Doctoral Networks
UPV/EHU Partner Status: Coordinator
UPV/EHU PI: Nicholas Ballard

Project start: 01/01/2023
Project end: 31/12/2026

Brief description: Machine learning (ML) systems continue to revolutionize many aspects of daily life, but despite their immense potential have yet to impact significantly in polymer science. One major issue that is hindering the more widespread use of machine learning in polymer science, and many other physical sciences, lies in the challenges in amassing sufficient data to efficiently train machine learning models. This in itself is not necessarily a problem, and is an issue frequently encountered in the machine learning field, but can only be resolved by a thorough understanding of the science behind the problem of interest. CINEMA aims to providing a training platform that will allow the next generation of polymer scientists to take polymer science into the 21st century through incorporating the fundamental knowledge gained over many years of research into the training of machine learning systems. Such a knowledge-driven machine learning approach puts the scientific issues of CINEMA at the forefront of the use of machine learning in fundamental scientific problems, and also provides the perfect training platform for the next generation of scientists, for whom the use of AI will be an invaluable tool.

MSCA Postdoctoral Fellowships (PF) projects

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MSCA COFUND projects