Summary
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.
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Web resources: | https://cordis.europa.eu/project/id/101072732 |
Start date: | 01-01-2023 |
End date: | 31-12-2026 |
Total budget - Public funding: | - 2 062 771,00 Euro |
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Original 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.Status
SIGNEDCall topic
HORIZON-MSCA-2021-DN-01-01Update Date
09-02-2023
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EU-Programme-Call
Horizon Europe
HORIZON.1 Excellent Science
HORIZON.1.2 Marie Skłodowska-Curie Actions (MSCA)
HORIZON.1.2.0 Cross-cutting call topics
HORIZON-MSCA-2021-DN-01
HORIZON-MSCA-2021-DN-01-01 MSCA Doctoral Networks 2021