Summary
Many of the main current economic and societal challenges in Europe are characterised by complex dynamic patterns stemming from path dependency, irreversibility, systemic risk and (local) interaction of heterogeneous agents. Examples in this respect are the search for appropriate policies to mitigate climate change, to foster a transition to a low-carbon economy, or to govern the development, diffusion and economic implications of new technologies. Designing sound economic policy in such domains is challenging and should be informed by empirical analyses and modelling frameworks that are suitable for capturing the complexity of the (economic) environment. The Innovative Training Network EPOC aims at advancing the state-of-the-art and the applicability of computationally intensive methods for decision and policy analysis and at using these methods in the domains of climate change and innovation. This agenda will be pursued by combining an interdisciplinary research agenda with an innovative European joint doctoral training programme. Early Stage Researchers will gain expertise and skills in data science, network theory, agent-based simulation, and economic modelling, with focus on climate change and innovation, and will apply these skills in their individual research projects. The academic training will be complemented by Transferable Skills Training Measures, Inter-Sectoral Training Measures, provided by non-academic partners, and Career Development Training. Interaction with stakeholders, policy makers and the general public will play an important role in pursuing the EPOC agenda and disseminating the results. The EPOC consortium consists of seven leading European universities and ten partner organisations. Each Early Stage Researcher will be hosted by two universities, will have a secondment with a partner organisation, and will graduate with a double degree.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/956107 |
| Start date: | 01-03-2021 |
| End date: | 28-02-2025 |
| Total budget - Public funding: | 3 982 061,52 Euro - 3 982 061,00 Euro |
Cordis data
Original description
Many of the main current economic and societal challenges in Europe are characterised by complex dynamic patterns stemming from path dependency, irreversibility, systemic risk and (local) interaction of heterogeneous agents. Examples in this respect are the search for appropriate policies to mitigate climate change, to foster a transition to a low-carbon economy, or to govern the development, diffusion and economic implications of new technologies. Designing sound economic policy in such domains is challenging and should be informed by empirical analyses and modelling frameworks that are suitable for capturing the complexity of the (economic) environment. The Innovative Training Network EPOC aims at advancing the state-of-the-art and the applicability of computationally intensive methods for decision and policy analysis and at using these methods in the domains of climate change and innovation. This agenda will be pursued by combining an interdisciplinary research agenda with an innovative European joint doctoral training programme. Early Stage Researchers will gain expertise and skills in data science, network theory, agent-based simulation, and economic modelling, with focus on climate change and innovation, and will apply these skills in their individual research projects. The academic training will be complemented by Transferable Skills Training Measures, Inter-Sectoral Training Measures, provided by non-academic partners, and Career Development Training. Interaction with stakeholders, policy makers and the general public will play an important role in pursuing the EPOC agenda and disseminating the results. The EPOC consortium consists of seven leading European universities and ten partner organisations. Each Early Stage Researcher will be hosted by two universities, will have a secondment with a partner organisation, and will graduate with a double degree.Status
SIGNEDCall topic
MSCA-ITN-2020Update Date
28-04-2024
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