PhD Studentship: Monitoring Complex Ecosystems - Critical Transitions in Time Series Soil Health and Earthquake

From the collapse of the Amazon rainforest to financial markets, from earthquakes to degraded farmland - complex systems in the natural and human world can shift suddenly and irreversibly. Understanding such critical transitions ranks among the most urgent challenges in modern ecosystem sciences and societal preparedness. This PhD project puts you at the frontier of detecting such transitions in time series, drawing from original data from soil and agriculture, as well as geohazards.

Although difficult to describe mathematically in their full multiscale complexity, many complex systems leave warning signals in their data - subtle mathematical fingerprints that appear before a rapid transition unfolds. But reading those signals is hard. Real-world data is noisy, assumptions don't always hold, and the stakes of getting it wrong are high.

You’ll use and help further develop an open-source Julia-based toolkit, developed by co-supervisor Dr George Datseris, to tackle this detection problem in two exciting, real-world settings:

Earthquakes. Can robust, consistently detectable signals in seismic data help us better understand the build-up towards earthquake rupture? You’ll apply cutting-edge dynamic systems methods to seismological time series to find out.

Soil ecosystems. Soils are complex, living systems that shift between states as seasons change, extreme weather hits, and agricultural practices evolve. You’ll analyse soil time series to track how these transitions happen, and what drives them.

Across both applications, a core challenge is distinguishing real transitions from statistical noise. You’ll build rigorous frameworks for quantifying confidence in what the data is actually telling us.

The ability to better assess tipping points in natural systems has profound implications for how humanity responds to climate change, manages land, and prepares for geohazards. This project bridges mathematics, earth science, and ecology to take on that challenge directly.

We welcome applicants from anywhere. You don't need to be an expert in all areas; curiosity and drive matter most. Strong candidates will have:

• A solid grounding in mathematical or physical sciences
• Interest in dynamical systems and complex system behaviour
• Some coding experience (Python and/or Julia)
• Enthusiasm for working across disciplines
• An independent, self‑motivated approach to research

You’ll gain skills spanning dynamical systems theory, data science, earthquake science, and soil ecology, working with large, real-world datasets throughout, and collaborating with the non‑profit organisation Earth Rover Program.

• This PhD position comes with funding for UK home tuition fee and living stipends
• For candidates with degrees from outside the UK, international tuition fees will need to be covered by other funding sources
• UK tuition fees and an annual tax‑free stipend of at least £21,805 per year

Ready to bridge mathematical sciences with complex ecosystems and societal relevance? We actively encourage applications from people of all genders, nationalities, and backgrounds. Diverse perspectives make better science.