Project Overview: Biodiversity loss is a critical global challenge, and effective ecosystem protection requires accurate, continuous, and large-scale data collection. However, many natural habitats are remote, fragile, or hazardous, making traditional fieldwork difficult. This PhD project, hosted at University College London, aims to revolutionize biodiversity monitoring by developing animal-inspired cognitive navigation for autonomous legged robots. These robots will be designed to safely and intelligently traverse wild environments, collecting ecological data with minimal disturbance to wildlife and habitats. Research Focus: The student will investigate how artificial intelligence and robotics can learn from nature, drawing inspiration from the remarkable navigation abilities of animals such as insects, mammals, and birds. The project will integrate biological strategies into robotic systems, enabling robots to perceive, plan, and adapt their movements in complex terrains like forests, grasslands, and wetlands. The goal is to create AI-driven legged robots capable of autonomous, non-invasive biodiversity monitoring, complementing traditional ecological surveys and reducing the environmental footprint of data collection. Interdisciplinary Training: The successful candidate will receive comprehensive training in robot perception, cognitive AI, and ecological applications. The project is supported by supervisors from UCL’s Intelligent Robotics Group and the Centre for Biodiversity and Environment Research, with opportunities for collaboration with leading organizations such as the Zoological Society of London and the UK Centre for Ecology & Hydrology. The training program includes a placement with an AI-INTERVENE project partner (3-18 months), as well as opportunities to present research at national and international conferences. Eligibility: This position is suitable for students with a background in robotics, computer science, artificial intelligence, engineering, or physical sciences. Candidates with experience or strong interest in machine learning, computer vision, or autonomous systems are encouraged to apply, as are those from environmental or biological sciences with computational or robotics experience. The project seeks enthusiastic individuals eager to apply AI to real-world biodiversity and ecological monitoring challenges. Funding: The studentship is fully funded by the AI-INTERVENE NERC Doctoral Focal Award, subject to a competitive selection process. This includes tuition fees and a stipend for living expenses. Application Process: Interested applicants should apply via the University College London application portal, referencing the AI-INTERVENE NERC Doctoral Focal Award. Prepare a CV and a statement of interest detailing relevant experience and motivation. Early contact with the supervisors is recommended for further information. The application deadline is January 19, 2026. Impact: By combining artificial intelligence with ecological expertise, this project aims to develop the next generation of environmentally integrated autonomous systems. The research will contribute to conservation robotics and sustainable exploration, enabling long-term monitoring and protection of ecosystems. The student will be at the forefront of interdisciplinary science, gaining skills and experience that open excellent future employment opportunities in academia, industry, and environmental organizations.