Analysis and mathematical modeling of complex networks in real-world economic, social and biological systems

1 Research Collaborator position

(Deadline January 5^th, 2023 13:00 )

Fields

Complex networks, complex systems, graph theory, data science

Profile

We are looking for an experienced scientist to conduct research at a high level in the analysis and modeling of real-world complex systems and networks. The ideal candidate has multidisciplinary background and past research trajectory, with expertise spanning multiple fields such as mathematics, physics, economics, biology or related. The candidate should have a solid knowledge of quantitative methodologies for the analysis of empirical network data and experience in the development of formal methods and mathematical models. The candidate should be able to independently design research projects that involve the analysis of real-world biological, neuronal, social, economic or technological networks. The candidate is expected to have international experience in research teams and an established network of expert collaborators.

Activity

The successful candidate will carry out research within the NETWORKS unit, whose main focus is the study of the structure, dynamics and physics of networks emerging from the intricate interconnectedness of the constituents of large complex systems. The NETWORKS unit combines a theoretical approach, largely based on statistical physics, information theory, discrete mathematics and sustainability science, with a data-driven approach informed by the empirical properties of real-world complex networks, especially those naturally emerging in financial, economic, social, ecological, neural and biological systems. The successful candidate's activity is expected to fully integrate within the NETWORKS unit's research landscape and foster the further expansion of the latter. Given the strong interdisciplinarity of the unit's research, a regular collaboration with national and international experts in various fields, especially mathematics, physics, computer science, neuroscience, biology, ecology, social science, economics and finance is expected. Collaboration with other research units at the IMT School is also welcome. The successful candidate will have the possibility of contributing to the Unit's PhD supervision and teaching activity within the IMT School's PhD program in Systems Science, especially the track in Complex Systems and Networks.

Formal requirements

PhD in Physics, Mathematics, Economics or related fields;
Excellent track record of interdisciplinary research on complex networks emerging in social, biological and economic systems, in terms of peer-reviewed publications and international conference presentation;
Excellent knowledge of English language, both written and spoken.

Specific requirements