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BiD4BEST

Financiado

Cerrado

Big Data applications for Black hole Evolution STudies

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... ver más

29/02/2024

SOUTHAMPTON

4M€

Presupuesto del proyecto: 4M€

Líder del proyecto

UNIVERSITY OF SOUTHAMPTON No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Ver 11 Participantes

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2024-02-29

MSCA-ITN-2019: Innovative Training Networks Objective:The Innovative Training Networks (ITN) aim to train a new generation of creative, entrepre...

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Este proyecto no cuenta con búsquedas de partenariado abiertas en este momento.

Información adicional privada

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11 Participantes

SOUTHAMPTON

606.35K€ | Lider

3M ESPAÑA

410.00K€ | Participante

UNIBO

523.00K€ | Participante

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Duración del proyecto: 54 meses Fecha Inicio: 2019-08-19
Fecha Fin: 2024-02-29

Líder del proyecto

UNIVERSITY OF SOUTHAMPTON No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 4M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto 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.

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