Ecological networks at multiple resolution levels: data and models

Ecological networks, food webs, graph theory

The research activity involves both the preparation of datasets of ecological networks observed at different resolution levels (such as different taxonomic, trophic, or spatial aggregation of nodes) and their modeling through random graph models that allow for a consistent multiscale description (e.g. derived from network renormalization schemes). The successful candidate will carry out research within the NETWORKS unit (https://networks.imtlucca.it), 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 complexity science, with a data-driven approach informed by the empirical properties of real-world complex networks, especially those naturally emerging in biological, neural, ecological, social, economic, financial, and technological 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.

• Research experience in data assemblage, (meta)data analysis, network science methods, preferably in the domain of ecological networks, food webs, mutualistic networks or other ecological data;
• Knowledge of network models, especially for ecological modeling.

1 year, renewable