Cilia-AI | European Training Program for Deconvolution of Multi-scale Cilia Function in Health and Disease by Integrating Machine Learning-AI Approaches.

Original description

Cilia-AI will train a new generation of multidisciplinary biomedical researchers and entrepreneurs, and those specializing in emerging machine learning technologies, a subset of AI. The focus is the study of primary cilia, microtubule-based projections on cell surfaces that play a pivotal role in coordinating cellular signalling pathways during development and homeostasis of cells, tissues and organs. These tiny structures are essential for various physiological functions such as hearing, smell, respiration, excretion and reproduction. Dysfunctional cilia can lead to >35 severe human diseases known as ciliopathies, exhibiting diverse and overlapping phenotypes, affecting up to 1 in 400 people. To unravel the multi-level organisation and regulation of cilia in health and disease, Cilia-AI employs a multidisciplinary approach, integrating cutting edge technologies like structural biology, omics- and organoid technologies. Advanced imaging techniques, including super-resolution microscopy, cryo-electron tomography and expansion microscopy, will be used to generate high-resolution and versatile datasets. Processing such data requires sophisticated computational methods. Cilia-AI is at the forefront of implementing and developing machine learning approaches to decipher these high-content datasets and integrate diverse multidisciplinary data. Cilia-AI offers unparalleled training opportunities for 15 Doctoral Candidates (DCs) in both academic and industrial settings. The training involves individual research projects, secondments, and network-wide sessions. This training equips DCs with skills attractive to both industrial and academic sectors, enhancing their career prospects in these domains. Overall, Cilia-AI’s research and training activities contribute to advancing the understanding of cilia in health and disease while fostering a new generation of skilled professionals with broad competences.

Status

SIGNED

Url

https://cordis.europa.eu/project/id/101169364

Call topic

HORIZON-MSCA-2023-DN-01-01

Update Date

23-12-2024