MSCA Network

International Research Centres

Fraunhofer Institute

• Role: Contribute data to the project, contribute their expertise in enabling efficient and sustainable transfer of scientific knowledge into commercial use. Exposure to a world-leading applied research environment. (see Table 1.2.a GA)

Course/workshops

• Advanced course: Multi-Criteria Decision Making in Sustainable Finance (M30, 3 ECTS): Principles of multi-criteria decision making. Various techniques and concepts (e.g., fuzzy set theory, analytical hierarchy process, preference modelling) to incorporate multiple objectives, in line with ESG principles
• Lab Training: Virtual reality lab, optimization lab, computer graphics and visualisation lab, analytics lab

DC secondments

• DC3: Industry standard for blockchain, WP4, M12 – M15: applied industry-research, contribute to multiple projects on blockchain and decentralized finance
• DC6: Collaborative learning across data silos, WP1, M12 - M15, applied industry-research, implement various use-cases
• DC7: Risk index for cryptos, WP4, M27 – M30, exposure to world-leading research centre and infrastructure, implementing a prototype solution
• DC9: Audience-dependent explanations, WP3, M27 – M30, improve know-how transfer by using and implementing advanced financial models
• DC15: Deep Generation of Financial Time Series, WP1, M18 – M21, applied industry-research, implementing several use-cases
• DC16: Investigating the utility of classical XAI methods in financial time series, WP3, M18 – M21, Research needs to be validated with industry to achieve the envisioned impact
• DC17: Fair Algorithmic Design and Portfolio Optimization under Sustainability Concerns, WP3, M18 – M21, for training in portfolio optimization in the presence of sustainability scenarios

(taken from Table 3.1.c GA)