SOURCE-LINKED INTELLIGENCE

Overcoming challenges in the evolution and nature of massive stars

CORDIS · observation · Publication date unknown

rk of researchers from Europe and America with expertise in various disciplines, and with background in both theory and observations. We will exploit the avalanche of public data archives and develop machine learning algorithms to detect massive stars in binary and multiple systems, classify them, and create statistically meaningful samples for diverse evolutionary states. We will develop progressive methods of signal processing for the analysis of the stellar properties, and cutting-edge numerical codes to unveil the impact of stellar interaction and mass ejection on the evolution of the stars and stellar systems. The acquired results will significantly enhance our knowledge and lead to major advancements in all related fields. The bulk of exchanges will be undertaken by PhD students and Postdocs, whom we will educate and train in modern observing and data analysing techniques, machine learning algorithms, and in high-performance computing, equipping them with excellent skills for their future careers. We will organise schools, workshops and educational activities to share knowledge

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recordType

award

status

SIGNED

region

EU

value

1614600

unit

EUR