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Big Data applications for Black hole Evolution STudies

Project description

DEENESFRITPL

Training network on black hole formation

The formation of supermassive black holes in galaxies is a prominent area of astrophysical research. Observational evidence indicates that nearly all large galaxies contain a supermassive black hole, located at their centre. Upcoming Space missions involving European teams will bring a wealth of new observational data; these will only be meaningful if there is synergy between observational astronomers and data analytics experts. With Marie Skłodowska-Curie funding, BiD4BEST will establish a training network composed of talented scientists in observational astronomy and big data analysts. The project will provide doctoral education that will touch upon state-of-the-art observations, cutting-edge numerical simulation methods and analytical tools. Research outcomes will shed further light on the physics of black hole formation during galaxy evolution.

Objective

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.

Fields of science

Programme(s)

Topic(s)

Call for proposal

H2020-MSCA-ITN-2019

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Funding Scheme

MSCA-ITN - Marie Skłodowska-Curie Innovative Training Networks (ITN)

Coordinator

UNIVERSITY OF SOUTHAMPTON
Net EU contribution
€ 606 345,12
Address
Highfield
SO17 1BJ Southampton
United Kingdom

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Region
South East (England) Hampshire and Isle of Wight Southampton
Activity type
Higher or Secondary Education Establishments
Links
Other funding
€ 0,00

Participants (9)

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EC signature date 19 August 2019
Last update: 31 December 2022

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Permalink: https://cordis.europa.eu/project/id/860744

European Union, 2023