A cross-disciplinary research framework at institution level and beyond

Rethinking and restructuring cross-disciplinary research requires innovative models and the Institute for Cross-Disciplinary Physics and Complex Systems (IFISC) stands as a powerful example. Since its creation, IFISC has grown fourfold, now hosting 90 researchers from 15 different countries. Its unique structure fosters collaborations and a shared sense of belonging, built on a common foundation in complex systems. By bridging diverse disciplines and providing cutting-edge training, IFISC is shaping the next generation of researchers while offering a blueprint for how to reorganize research resources to foster cross-disciplinary research at institution levels and beyond.

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Publication Details

Journal
Nature Communications
Published
2024-11-29
DOI
https://doi.org/10.1038/s41467-024-54703-2
Citations
2
Primary Topic
Neural Networks and Reservoir Computing
Type
article
Field-Weighted Citation Impact
0.69

Funders

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article

A cross-disciplinary research framework at institution level and beyond

Apostolos Argyris, M. San Miguel, Emilio Hernández-Garcı́a
2 citations
Nature Communications
Neural Networks and Reservoir Computing
0.69
article

A cross-disciplinary research framework at institution level and beyond

Apostolos Argyris, M. San Miguel, Emilio Hernández-Garcı́a
article en
2 citations

Abstract

Rethinking and restructuring cross-disciplinary research requires innovative models and the Institute for Cross-Disciplinary Physics and Complex Systems (IFISC) stands as a powerful example. Since its creation, IFISC has grown fourfold, now hosting 90 researchers from 15 different countries. Its unique structure fosters collaborations and a shared sense of belonging, built on a common foundation in complex systems. By bridging diverse disciplines and providing cutting-edge training, IFISC is shaping the next generation of researchers while offering a blueprint for how to reorganize research resources to foster cross-disciplinary research at institution levels and beyond.

Nature CommunicationsVol. 15(1)
Institute for Cross-Disciplinary Physics and Complex Systems (ES)
Instituto de Física Interdisciplinar y Sistemas Complejos, Agencia Estatal de Investigación
Openalex Percentile: Top 23%
Neural Networks and Reservoir Computing
0.69
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