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

About the Role

& Team

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.

Key Responsibilities

• Benchmark and fine-tune state-of-the-art monocular depth-estimation models using camera-trap imagery.
• Develop and evaluate AI-based methods for single-image 3D reconstruction of animals, integrating metric depth information to recover body dimensions and shape in real-world units.
• Curate and manage colour, LiDAR, photogrammetry and 3D datasets.
• Develop robust, reproducible computational pipelines using Python and relevant deep-learning frameworks.
• Undertake quantitative validation, statistical analysis and evaluation of model performance, accuracy and uncertainty.
• Collaborate with project partners to undertake data collection and validation at Chester Zoo.
• Contribute to the development and release of open-source software, datasets and trained models.
• Prepare research findings for publication in peer-reviewed journals and presentation at national and international conferences.
• Contribute to project management, dissemination, stakeholder engagement and the development of follow-on funding applications, including Phase 2 of the NERC AI4ES programme.

Key Skills & Experiences

We are looking for a highly motivated researcher with strong computational skills and experience in computer vision, machine learning, AI-based image analysis and/or 3D reconstruction. We welcome applicants from a broad range of disciplinary backgrounds; previous experience in ecology or zoology is not required. This is an interdisciplinary project, and we recognise that relevant expertise can be developed through a variety of research backgrounds and career pathways. We therefore encourage applications from candidates who bring transferable skills and enthusiasm for the project, even if they do not meet every criterion listed below.

Essential criteria:

• A PhD (or close to completion) in a relevant discipline, such as Computer Science, Artificial Intelligence, Machine Learning, Robotics, Computational Biology, Neuroscience, Engineering or another quantitative or computational discipline.
• Strong programming skills in Python.
• Practical experience with deep-learning frameworks such as PyTorch, TensorFlow or equivalent.
• Research experience developing, adapting and/or evaluating computer-vision or machine-learning models.
• Experience of quantitative analysis and rigorous evaluation of computational methods.
• Evidence of making a demonstrable, independent contribution to research projects.
• Excellent written and verbal communication skills, with the ability to work effectively within an interdisciplinary research team.
• Excellent organisational skills, attention to detail and the ability to manage research activities and deadlines.
• Ability to travel to Chester Zoo and undertake on-site data collection.

To learn more about role and requirements, please read the Job Description provided below.