Publisher
source

S Durant

3 months ago

Developing AI for the Global Monitoring of Big Cats: Cheetah as a Case Study University of Reading in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Funded PhD Project (Students Worldwide)

Deadline

Expired

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Country

United Kingdom

University

University of Reading

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Keywords

Computer Science
Data Science
Machine Learning
Ecology
Environmental Science
Biology
Remote Sensing
Zoology
Geography
Artificial Intelligence
Biodiversity
Habitat Management
Conservation
Wildlife Trade
Data-analysis
Geospatial Information Systems

About this position

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.

Funding details

Funded PhD Project (Students Worldwide)

What's required

Applicants should hold a first-class or upper second-class undergraduate degree in a relevant field such as computer science, ecology, biology, environmental science, or a related discipline. Experience or strong interest in artificial intelligence, machine learning, data science, GIS, or remote sensing is highly desirable. Candidates should demonstrate analytical skills and a passion for conservation. English language proficiency is required for non-native speakers, typically evidenced by IELTS or equivalent.

How to apply

Interested candidates should visit the project link and follow the application instructions provided by UCL. Prepare your CV, academic transcripts, and a cover letter outlining your suitability for the project. Contact the supervisors for further information if needed.

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