Host Faculty: Engineering
General Subject Area: Mechanical Engineering
Project Level: PhD
Biodiversity is declining globally, yet our ability to monitor ecosystems at scale remains limited. Conventional surveys are labour-intensive, spatially sparse, uneven, and hard to sustain over ecologically relevant timescales. This project develops passive acoustic methods to map the sounds of nature across space and time, localising and characterising the calls of native and invasive species to move beyond simple detection and toward spatial ecological insight that can inform conservation decisions at the ecosystem scale.
A key innovation in this project is the integration of microphone arrays with state-of-the-art machine learning and sound-source localisation techniques to accurately detect and position vocalising animals within natural environments. The resulting acoustic maps will support biodiversity assessment and inform conservation initiatives such as predator control, native forest regeneration, and the protection of crops and orchards from pest species. Building on the Listening Lab's internationally recognised expertise in computational bioacoustics, passive acoustic monitoring, data-efficient machine learning, annotation tools, and localisation pipelines, the project will advance both algorithmic performance and computational scalability. Combining field experimentation, acoustic sensor deployment, and development of computational methods, the research will deliver practical tools for monitoring ecosystems and demonstrate their effectiveness through real-world field implementations.
Supervisors
Primary Supervisor: Stefanie Gutschmidt
Other Supervisor(s): Sara Kross
Key qualifications and skills
Signal processing, machine learning, computer science, python coding, data processing, managing large data sets, statistic (useful not required)
Does the project come with funding
Per annum: Stipend of $32,650 plus PhD tuition fees. The project also has up to $5,000 available for research expenses across the duration of the degree.
Funding duration: Three years (360 points)
Final date for receiving applications
27 October 2026
How to apply
This is a UC Commitments Doctoral Scholarship and applications must be made through the Scholarship Portal in your myUC account. Emailed applications will not be considered. Find out more here: University of Canterbury Scholarship Portal - UC Commitments - Mapping the Sounds of Nature: Scalable Computational Bioacoustics for Biodiversity Monitoring through Sound Localisation
Keywords
biodiversity, passive acoustic monitoring, bio/eco-acoustics, sound localisation, microphone arrays, machine learning
