PhD Studentship: NatureNet: AI Systems for Conservation and the Management of Human-wildlife Conflict

Oxford Brookes University - Faculty of Health, Science and Technology - School of Engineering, Computing and Mathematics, and School of Biological and Medical Sciences

3 Year, full-time PhD studentship

Eligibility: Open to home, EU and international students

Bursary p.a.: £20,780

University fees and bench fees: This studentship will cover university fees. Visas and associated costs are not covered.

Closing date: 20th February 2026

Interviews: TBC (online)

Start date: September 2026

Project Title: NatureNet: AI systems for conservation and the management of human-wildlife conflict

Director of Studies: Dr Matthias Rolf

Supervisors: Dr Miya Warrington, Dr Shadi Eltanani

Contact: Dr Matthias Rolf (mrolf@brookes.ac.uk)

Requirements:

Entry requirements:

Applicants should have a first or upper second-class honours degree from a Higher Education Institution in the UK or acceptable equivalent qualification.

English language requirements:

International/EU applicants must have a valid IELTS Academic test certificate (or equivalent) with an overall minimum score of 6.0 and no score below 5.5 issued in the last 2 years by an approved test centre.

Project Description:

Human-wildlife conflict is widespread, yet current monitoring systems aiming at their reduction remain costly, vulnerable, and difficult to scale. This project will focus on computational and engineering innovation by developing wildlife tracking technologies, including integrating advanced AI-based analytics to create a novel prototype for conflict mitigation. The work will involve developing a data processing pipeline capable of handling complex behavioural datasets from biologgers and autonomous monitoring units, enabling accurate movement and interaction analysis without reliance on GPS-based technology. In the final phase, the prototype will be tested in real-world conditions such as involving predators and/or semi-domesticated livestock, in collaboration with local and Indigenous stakeholders (Europe, the Global South). This project develops novel computational methods to meet conservation needs, delivering a transformative solution for reducing human-wildlife conflict.

This project would suit individuals with an interest in technology development and computational methods to be applied towards wildlife monitoring and conservation.

The student will join two complementary research environments: The C-Wild Warrington lab (Ecology and Conservation) and the Machine Learning and Robotics research group (Artificial Intelligence, Data Analysis and Systems). This will provide interdisciplinary training, enabling the student to integrate ecological knowledge with advanced computational methods for developing and testing innovative wildlife monitoring solutions.

The student should have strong computational skills, including programming (Python or similar), data analysis, and familiarity with machine learning for time-series and sensor data. Basic knowledge of designing and building electronic units (e.g., biologgers, IoT systems), experience managing large datasets, and prior exposure to working in wild or remote field settings are essential.

The studentship requires you to undertake the equivalent of up to 6 hrs of teaching per week on average, during semester time, and to include preparation and marking (but no more than 20 hrs per week), and to participate in a teaching skills course without further remuneration.

Application process

Apply directly via the university portal (via the above 'Apply' button). Please include the following in your application:

• A cover letter
• A CV
• Details of two referees, at least one from an academic background
• A research proposal
• Copies of your previous degree certificates and transcripts
• A scan of your passport
• Evidence of a valid IELTS or other valid English language qualification, in line with Oxford Brookes’ requirements (international and EU candidates only)

For any queries, please contact tde-tdestudentships@brookes.ac.uk