Category Archives: Call

New Paper on Sampling Social Media + Call for Abstract @ Networks21 Satellite

NERDS member Michele Coscia is having a busy March!

He published a new paper in the TKDD journal titled “Noise Corrected Sampling of Online Social Networks“. The paper focuses on a new way to perform topological network sampling, i.e. to explore a network by following its edges such that the explored (sub)network is as similar as possible to the whole structure. In this paper, the method uses a Bayesian framework to estimate the amount of novel information a new connection brings about into the currently explored sample.

He is also organizing a satellite for the Networks21 conference. The satellite is titled “Complex Networks in Economics and Innovation”. The organizers are looking for contributed abstracts on network applications on research about economic development and innovation. Read more on the official website, or submit your abstract to the submission site.

Open Positions

With NERDS winning grants and growing, we have added a Positions page at https://nerds.itu.dk/positions/, currently featuring 2 open calls at ITU that are directly relevant to us as they can lead to NERDS positions. If your research overlaps with ours and you are interested get in touch!

1) PhD Open Call 2021

The ITU-wide PhD Open Call 2021, deadline March 10th, features 2 potential PhD projects by NERDS members:
1) Michael: Network analysis of urban transport networks for a green transition from car- centricity to cycling
2) Michele+Luca: Modelling Complex Social Systems to Handle Disinformation

2) Asst./Assoc. Professor in data science and machine learning

This computer science department wide call, deadline March 29th, is looking for applicants in any of these areas, including NERDS topics:

  • Data mining, large-scale data analysis, data visualization
  • Machine learning
  • Natural language processing
  • Network science, analysis of large (social and other) networks
  • Bioinformatics
  • Computer vision, signal analysis
  • Computational social science
  • Fairness and accountability in data science and machine learning
  • Statistics, computational statistics, probabilistic modelling

Watch this space and stay tuned for more. 🤓

Special issue “Complex Networks and Economics”

We are inviting contributions to the “Complex Networks and Economics” issue of the Frontiers in Big Data journal, co-edited by NERDS Michele Coscia and the NERDS-friendly and really excellent Morgan Frank, recently appointed assistant professor at the University of Pittsburgh.
 
 
Some additional information about what we’re looking for:
 

We think it is important to lift people out of poverty and to guarantee them decent standards of living. However, to successfully promote economic growth, the high degree of complexity of the global market and regional industrial activities requires an integrated understanding of the ecosystem of complementary actors, knowhow, and capital. The way to do so is by conceptualizing productivity as an emerging property of a complex system made by simpler interacting parts. Complex systems are notoriously difficult to control but quantifying these interactions can identify the bottlenecks to growth and inform policy to bolster economic convergence. Using tools from economics, complex systems, and network science, we seek crucial insights that enable economic convergence. 

The goal of this Research Topic is to collect contributions using complex network analysis to model economic systems and to gain insights into economic development which has proven to be a valuable scientific undertaking. We want to explore the potential applications of complex network analysis to foster our understanding of complex economic systems. We welcome contributions in the broad areas of:

• Mapping the relationship of complex economic activities to build Product and Industry Spaces at the global, regional, and local level;
• Tracking flows of knowhow in all its forms (business travels, social interrelationships between entrepreneurs, etc);
• Creating networks of related tasks and skills to estimate knockoff effects and productivity gains of automation;
• Investigating the dynamics of innovation via analysis of patents and inventions;
• Uncovering scaling laws and other growth trends able to describe the systemic increase in complexity of activities due to agglomeration, e.g. in cities;
• In general, any application of network analysis that can be used to further our understanding of economics.

 
We’re looking forward to your contributions!

Postdoc wanted!

Update 2019-06-21: This application is now closed.

We are looking for a postdoc in data/network science, to start in fall 2019. The postdoc will work in the NEtwoRks, Data, and Society (NERDS) group at IT University of Copenhagen with Roberta Sinatra and Michael Szell. The group currently focuses on quantitative projects at the boundary of computational social science and network science, including science of science, social dynamics, urban sustainability, data visualization, and fundamental questions in complex systems.

We seek a researcher with strong quantitative background in fields such as statistical physics, applied mathematics, machine learning, network analysis, complex systems, urban computing, or other closely related fields. Our priority is to attract technically strong researchers who are interested in asking bold, new questions with data. A stated passion and experience in data analysis is a must, including excellent programing skills in Python or a similar language and experience handling large data sets.

The initial length is 12 months, full-time, with possibility to extend up to 3 years. Apart from research, a moderate amount of co-teaching is expected within the Data Science program. Postdoc salaries in Denmark are determined according to the collective agreement for academic staff employed by the State Sector. Researchers from abroad can request a reduced researcher taxation scheme.

If you are interested please contact Roberta Sinatra at rsin@itu.dk.