Difference between revisions of "MSCA Network"

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== EIT Digital ==
 
== EIT Digital ==
 
== Fraunhofer Institute ==
 
== Fraunhofer Institute ==
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The Fraunhofer Institute is expected to contribute data to the project, contribute their expertise in enabling efficient and sustainable transfer of scientific knowledge into commercial use, and exposing the ESRs to a world-leading applied research environment.
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=== Course/workshops host ===
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Advanced course: Multi-Criteria Decision Making in Sustainable Finance (M30, 3 ECTS)
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=== ESR host: ===
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*[[https://wiki.fin-ai.eu/index.php/MSCA_Individual_Research_Projects#Industry_standard_for_blockchain ESR 3]]: Industry standard for blockchain (M12 – M15)
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*ESR 6: Collaborative learning across data silos (M12 – M15)
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*ESR 7: Risk index for cryptos (M27 – M30)
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*ESR 9: Audience-dependent explanations (M27 – M30)
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*ESR 15: Deep Generation of Financial Time Series (M18 – M21)
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*ESR 16: Investigating the utility of classical XAI methods in financial time series (M18 – M21)
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*ESR 17: Fair Algorithmic Design and Portfolio Optimization under Sustainability Concerns (M18 – M21)
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= European Central Bank =
 
= European Central Bank =

Revision as of 15:24, 26 October 2023

Universities

University of Twente

WU Vienna

HU Berlin

Bucharest University of Economic Studies

Babes-Bolyai University

Bern Business School

Kaunas University of Technology

University of Naples

Industrial Partners

Deloitte

Swedbank

Intesa Sanpaolo

Raiffeisen Bank

Cardo AI

Royalton Partners

International Research Centres

ARC Greece

EIT Digital

Fraunhofer Institute

The Fraunhofer Institute is expected to contribute data to the project, contribute their expertise in enabling efficient and sustainable transfer of scientific knowledge into commercial use, and exposing the ESRs to a world-leading applied research environment.

Course/workshops host

Advanced course: Multi-Criteria Decision Making in Sustainable Finance (M30, 3 ECTS)

ESR host:

  • [ESR 3]: Industry standard for blockchain (M12 – M15)
  • ESR 6: Collaborative learning across data silos (M12 – M15)
  • ESR 7: Risk index for cryptos (M27 – M30)
  • ESR 9: Audience-dependent explanations (M27 – M30)
  • ESR 15: Deep Generation of Financial Time Series (M18 – M21)
  • ESR 16: Investigating the utility of classical XAI methods in financial time series (M18 – M21)
  • ESR 17: Fair Algorithmic Design and Portfolio Optimization under Sustainability Concerns (M18 – M21)

European Central Bank