Senior Research Associate in Computer Vision and 3D Reconstruction Wildlife Conservation

Manchester Metropolitan University is one of the UK's largest universities, with a strong commitment to interdisciplinary research addressing real-world challenges. Our newly established School of Biological and Chemical Sciences, within the Faculty of Science and Engineering, brings together expertise spanning biodiversity, zoology, ecology, physiology and the biomedical sciences. The University has growing strengths in artificial intelligence, data science and computational research, supported by its new Centre for Digital Data Research (CDDR).

Together, these strengths provide an exciting environment for research at the intersection of AI, biological sciences and conservation.

You will join the School's Biodiversity and Environmental Resilience research group, where researchers investigate animal biology, evolution, behaviour and conservation, and develop innovative approaches to understanding and protecting the natural world. Our research combines traditional biological expertise with emerging technologies, including artificial intelligence, advanced 3D imaging and computational modelling. You will benefit from access to specialist research facilities, including imaging equipment in the University's new £1m Centre for Digital Modelling and Analysis for Cultural Heritage (D-MACH), and opportunities to engage with the wider Species Biology and Conservation (SBAC) research community through seminars, collaborative activities and knowledge exchange.

This position is funded by the National Environment Research Council (NERC) through Phase 1 of its Artificial Intelligence for Environmental Science (AI4ES) programme. The project, Using Camera Trap Images to Reconstruct Wildlife 3D Body Size and Condition, aims to develop innovative AI-based methods for measuring animal size, shape and body condition from standard camera-trap photographs.

By combining monocular depth estimation with single-image 3D reconstruction, the project will develop new approaches to recovering quantitative, real-world measurements of wild animals without the need for physical handling. Working with Chester Zoo and the Max Planck Institute for Evolutionary Anthropology, we will develop and validate these methods using advanced 3D imaging techniques, including LiDAR and photogrammetry, with the longer-term aim of supporting non-invasive wildlife health monitoring and conservation.

The project is led by Dr Charlotte Brassey (Principal Investigator), alongside Manchester Met colleagues Dr Selvino de Kort and Dr Bradley Cain, and external collaborators Dr Peng Wang (University of Sussex), Dr Lisa Holmes (Chester Zoo) and Dr Adam van Casteren (Max Planck Institute for Evolutionary Anthropology).

You will play a central role in the day-to-day technical development and delivery of the project, with responsibility for developing, testing and validating AI-based approaches to reconstructing animal body size and shape from camera-trap imagery. Your work will primarily involve computational research, including model development, dataset curation and quantitative analysis, alongside opportunities for practical data collection and validation at Chester Zoo.

You will be encouraged to take ownership of your research, contribute to peer-reviewed publications and conference presentations, and help shape future research directions, including the development of a larger Phase 2 funding application. You will also become part of the wider Biodiversity and Ecosystem Resilience research community, with opportunities to participate in the Species Biology and Conservation (SBAC) seminar series and professional development activities.

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