Center for Collective Learning at Corvinus University is a new interdisciplinary laboratory at Corvinus University using data science tools to understand the dynamics of knowledge in countries, cities, and firms. The lab will use data science and machine learning methods to explore questions of economic complexity, city science, and organizational mapping. The lab is supported by a five year European Research Executive Agency (ERA) award designed to increase the opportunities for eligible countries to attract and maintain talent.
Center for Collective Learning at Corvinus University’s mission is to develop knowledge and tools enhancing our understanding of the spatial and temporal organization of knowledge.
The lab, established in 2023, will work in economic complexity, involving the creation of new datasets and techniques that can help us understand the growth and distribution of knowledge in countries, cities, and regions; Urban data science, using networks and machine learning techniques to understand how knowledge is organized in cities; and organizational mapping, focused on the creation of tools that can help identify knowledge networks and flows within an organization.
The lab will be led by César A. Hidalgo, a Chilean-Spanish-American scholar known for his contributions to economic complexity, data visualization, and applied artificial intelligence. He is the founding director of the Center for Collective Learning at Corvinus University, and holder of the ERA Chair. Hidalgo also leads the Center for Collective Learning at the University of Toulouse (where he holds an ANITI Chair) and is an Honorary Professor at the University of Manchester’s Business School and a Visiting Professor at Harvard’s School of Engineering and Applied Sciences.
Between 2010 and 2019 Hidalgo led MIT’s Collective Learning group. Prior to working at MIT, Hidalgo was a research fellow at Harvard’s Kennedy School of Government (HKS). Hidalgo is also a founder of Datawheel, an award winning company with 10 years of experience in the creation of data distribution and visualization systems. He holds a PhD in Physics from the University of Notre Dame and a Bachelor in Physics from Universidad Católica de Chile.
“I am very excited for the opportunity to lead a new team exploring the boundaries of knowledge. Corvinus University is at the heart of a European city with one of the greatest cultural and scientific heritages. I will do my best to make the CLDL a place for creativity, learning, entrepreneurship, and exploration.”
Hidalgo’s contributions have been recognized with numerous awards, including the 2018 Lagrange Prize and three Webby Awards. Hidalgo is also the author of dozens of peer-reviewed papers and of three books: Why Information Grows (Basic Books, 2015), The Atlas of Economic Complexity (MIT Press, 2014), and How Humans Judge Machines (MIT Press, 2021).
We are looking for motivated, curious, and creative minds to join our team. We are opening several positions.
Open Academic Positions
We are looking for an Assistant Professor with research and teaching experience in Data Science. The Collective Learning Data Lab will support this position until the end of 2027 and will provide a starting package consisting of two PhD students and one Postdoc (to be hired by the Assistant professor in early 2024).
We will be posting details about this position in March 2023
We are looking for two postdocs with a PhD in Physics, Computer Science, Economics, or a related field. This is a 30 month (2.5 years) postdoc at the CLDL in Budapest.
More information about this position can be found here.
Open Staff Positions
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More positions will open in 2024.
This project has received funding from the European Union’s Horizon Europe ERA Chair programme under grant agreement No 101086712.
Disclaimer: The European Commission’s support for the production of this publication does not constitute an endorsement of the contents, which reflect the views only of the authors, and the Commission cannot be held responsible for any use which may be made of the information contained therein.