BiD4BEST | Big Data applications for Black hole Evolution STudies

Summary
The BiD4BEST ITN will offer doctoral training in one of the most visible areas of astrophysical research, the formation of supermassive black holes in galaxies. A coordinated research training effort in this field is needed now to mobilise the community in Europe and prepare a core group of young scientists in anticipation of new observational data in the early/mid 2020s from future space missions with strong European involvement. These data will have the quality and volume to yield transformational science on the formation of black-holes in galaxies, as long as the necessary expertise and synergies among observation, theory and data analytics exist within the European astronomy community. We propose to achieve this goal by setting up a research training network that brings together leading scientists in observational and theoretical studies of black holes and galaxies, industrial experts in cutting-edge big-data technologies, and professionals in science dissemination. Together, we will setup doctoral research projects each of which combines state-of-the-art observations, numerical simulations and innovative analytic tools to compare theory with observation and shed light on the physics of black hole formation in the context of galaxy evolution. The training on expertise from different research areas (observational astronomy, theoretical astrophysics) and sectors (academic, industrial) will be achieved by carefully designed secondments, mixed doctoral supervisory committees (academia, industry), well coordinated events for team communication and interaction, as well as network-wide courses on astrophysics and transferable skills. The proposed research training programme aspires to generate individuals that in addition to academic competences, master big-data analytics and have the capacity to apply these technologies to solve problems in different sectors (research, industry, non-academic) by developing innovative products and services.
Unfold all
/
Fold all
More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/860744
Start date: 01-03-2020
End date: 29-02-2024
Total budget - Public funding: 3 503 442,60 Euro - 3 503 442,00 Euro
Cordis data

Original description

The BiD4BEST ITN will offer doctoral training in one of the most visible areas of astrophysical research, the formation of supermassive black holes in galaxies. A coordinated research training effort in this field is needed now to mobilise the community in Europe and prepare a core group of young scientists in anticipation of new observational data in the early/mid 2020s from future space missions with strong European involvement. These data will have the quality and volume to yield transformational science on the formation of black-holes in galaxies, as long as the necessary expertise and synergies among observation, theory and data analytics exist within the European astronomy community. We propose to achieve this goal by setting up a research training network that brings together leading scientists in observational and theoretical studies of black holes and galaxies, industrial experts in cutting-edge big-data technologies, and professionals in science dissemination. Together, we will setup doctoral research projects each of which combines state-of-the-art observations, numerical simulations and innovative analytic tools to compare theory with observation and shed light on the physics of black hole formation in the context of galaxy evolution. The training on expertise from different research areas (observational astronomy, theoretical astrophysics) and sectors (academic, industrial) will be achieved by carefully designed secondments, mixed doctoral supervisory committees (academia, industry), well coordinated events for team communication and interaction, as well as network-wide courses on astrophysics and transferable skills. The proposed research training programme aspires to generate individuals that in addition to academic competences, master big-data analytics and have the capacity to apply these technologies to solve problems in different sectors (research, industry, non-academic) by developing innovative products and services.

Status

SIGNED

Call topic

MSCA-ITN-2019

Update Date

28-04-2024
Images
No images available.
Geographical location(s)
Structured mapping
Unfold all
/
Fold all
Horizon 2020
H2020-EU.1. EXCELLENT SCIENCE
H2020-EU.1.3. EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions (MSCA)
H2020-EU.1.3.1. Fostering new skills by means of excellent initial training of researchers
H2020-MSCA-ITN-2019
MSCA-ITN-2019