UOC - postdoctoral call 2025
The Complex Systems group at Universitat Oberta de Catalunya (CoSIN3) is seeking researchers at the postdoctoral level, to work on one (or both) of the research lines currently active in the group:
Structure and dynamics of Urban Complex Systems
Sidewalk networks and pedestrian dynamics: Analyzing the structure and usage patterns of pedestrian infrastructure to understand pedestrian movement, optimize walkability, and related issues like pollution exposure.
Dynamics of transportation systems: Studying emergent behaviors of urban transportation systems, such as congestion and disruptions, including multimodal transportation networks.
City resilience: Assessing the ability of urban systems to withstand and recover from shocks and stresses, such as natural disasters, economic downturns, and pandemics.
Mutualistic Networks (not only in Ecology)
Developing and implementing automated monitoring systems: We design and deploy automatic camera systems equipped with deep learning algorithms to monitor plant-pollinator interactions in the field. This technology allows us to capture both diurnal and nocturnal interactions, providing a comprehensive view of pollination dynamics.
Analyzing the structure of mutualistic networks: We investigate the emergent patterns in natural (e.g., plants and pollinators) and social (e.g., users and hashtags) ecosystems, focusing on nestedness, modularity, and in-block nestedness. We explore how these patterns affect, for example, the stability and feasibility of mutualistic communities.
Understanding the dynamics of mutualistic interactions: We study how plant-pollinator networks change over time, and how these changes affect the persistence of species and the functioning of ecosystems. We use computational models to simulate the dynamics of these networks and explore the impact of environmental changes.
Developing new methods for network analysis: We develop new analytical and computational tools to study the structure and dynamics of mutualistic networks, e.g. methods for bipartite network randomization and pattern detection.
Qualifications: PhD in network science, physics, big data, behavior modeling, urban science, complex systems, or related field. PhD is required by the start of the appointment. Programming (Python, Matlab, C), statistics, and data science skills are essential.
Candidates who wish to apply must contact first Dr. Javier Borge-Holthoefer (jborgeh@uoc.edu).