Hacking Urban Habitability: A Data-Driven Network Approach to Build Thriving Cities for All Species

Are you driven by the urgent need to reimagine our cities as thriving, equitable ecosystems for all life? We are seeking a curious and computational PhD candidate to pioneer a novel framework for urban habitability at the critical interface of ecological resilience and human wellbeing. This project will break new ground by moving beyond traditional spatial mapping to model the city as a complex, interacting system of human and non-human networks.

Your research will be anchored in a dynamic analysis of Leeds, UK. You will begin by applying the Accessible Natural Green Space (ANGSt) model, innovatively defining ‘accessibility’ and ‘naturalness’ to critique and enhance these metrics. This foundational map will be analysed against key human health indices (e.g., diabetes, mental health, poverty) to quantify socio-ecological disparities. But we will go much further. Leveraging big data from the Global Biodiversity Information Facility (GBIF), you will transform point-occurrence records of species into intricate spatial networks. This is where your work becomes truly innovative: you will develop and apply a new ‘network patterns biodiversity analysis,’ where the nearest-neighbour distances between ecological observations are reconceptualised as a network of functional connections. This allows us to move from static points to dynamic networks, analysing their topology, resilience, and fragmentation.

Guided by the latest conceptual frameworks for coupled social-ecological systems, your core mission will be to fuse these human health and biodiversity networks into a single, spatially explicit model in a new R package. You will investigate the bidirectional feedback loops between them: how does the configuration of the human settlement network (its roads, urban patches, and traffic flows) directly dictate the functional connectivity of species’ habitat networks? Conversely, how does the quality and connectivity of the habitat network influence human health outcomes, creating feedback that could—or should—inform urban planning? This model will allow you to simulate future scenarios, testing how urban development policies either rupture or repair these vital connections.

This PhD is an opportunity to develop exceptional skills in spatial ecology, complex network analysis, and big data computation while directly addressing the intertwined crises of climate change, biodiversity loss, and public health inequality. You will be part of a visionary, interdisciplinary team dedicated to creating actionable science for building healthier, wilder, and more just cities. If you are ready to transform how we see, study, and plan urban environments, we encourage you to apply.