Developing AI for the Global Monitoring of Big Cats: Cheetah as a Case Study

This PhD opportunity, hosted at University College London (UCL), focuses on developing artificial intelligence (AI) tools for the global monitoring of big cats, using the cheetah as a case study. Big cats are experiencing significant declines across their natural ranges, and scalable monitoring solutions are urgently needed to inform conservation strategies, support community coexistence, restore connectivity, protect habitats, and combat illegal wildlife trade. The project is part of the AI-INTERVENE department and will integrate cutting-edge research in biodiversity, ecology, zoology, artificial intelligence, data science, machine learning, geographical information systems (GIS), remote sensing, and data analysis. The successful candidate will work on designing and implementing AI-driven approaches to collect, process, and analyze ecological and spatial data, with the aim of improving conservation outcomes for cheetahs and other big cat species. Supervision will be provided by a multidisciplinary team: Professor S Durant, Associate Professor A Patel, and Dr. B Evans, who bring expertise in conservation biology, AI, and data science. The project offers a unique opportunity to collaborate across disciplines and institutions, leveraging advanced technologies to address real-world conservation challenges. Applicants should have a strong academic background in a relevant field such as computer science, ecology, biology, or environmental science, and demonstrate interest or experience in AI, machine learning, GIS, or remote sensing. Analytical skills and a passion for wildlife conservation are essential. English language proficiency is required for non-native speakers. While funding details are not specified, candidates are encouraged to check the project link for updates and contact the supervisors for further information. The application deadline is 19 January 2026, providing ample time to prepare a competitive application. This position is ideal for students seeking to make a tangible impact on global conservation efforts through innovative research and technology.