Senior Research Associate in Computer Vision and 3D Reconstruction
Develop innovative AI and computer vision methods to measure wildlife body size and condition from camera-trap imagery.
Best for:Best for computer vision researchers with strong Python and deep learning skills interested in applying AI to wildlife conservation.
Overview
Manchester Metropolitan University is seeking a Senior Research Associate to join the Biodiversity and Environmental Resilience research group within the School of Biological and Chemical Sciences. Funded by the Natural Environment Research Council (NERC), the project focuses on creating AI-based approaches for single-image 3D reconstruction and monocular depth estimation to assess wild animal morphology without physical handling. Working alongside partners such as Chester Zoo and the Max Planck Institute for Evolutionary Anthropology, the successful candidate will drive technical model development and dataset curation. The role offers an exciting opportunity to apply advanced computational techniques directly to conservation science and non-invasive wildlife monitoring.
What you'll do
- Benchmark and fine-tune state-of-the-art monocular depth-estimation models using camera-trap images.
- Develop and evaluate AI-based methods for single-image 3D reconstruction of animals to recover body dimensions in real-world units.
- Curate, manage, and process colour, LiDAR, photogrammetry, and 3D datasets.
- Build robust and reproducible computational pipelines using Python and deep learning frameworks.
- Perform quantitative validation, statistical analysis, and evaluation of model performance and uncertainty.
- Collaborate with external project partners to conduct field data collection and validation at Chester Zoo.
- Contribute to the release of open-source software, datasets, and trained models.
- Prepare research findings for publication in peer-reviewed journals and presentation at international conferences.
- Assist in project management, stakeholder engagement, and the development of follow-on funding applications.
Requirements
Degree required: PhD or close to completion in Computer Science, Artificial Intelligence, Machine Learning, Robotics, Computational Biology, Neuroscience, Engineering, or a related quantitative discipline
Language: English; excellent written and verbal proficiency
Instruction: English
Publications: Evidence of contribution to research projects; peer-reviewed publication record expected commensurate with career stage.
- Strong programming skills in Python
- Practical experience with deep learning frameworks such as PyTorch or TensorFlow
- Demonstrated research experience in developing, adapting, or evaluating computer vision or machine learning models
- Experience with quantitative analysis and rigorous evaluation of computational methods
- Evidence of making independent and demonstrable contributions to research projects
- Excellent written and verbal communication skills for effective interdisciplinary teamwork
- Strong organisational skills with attention to detail and ability to manage research deadlines
- Ability to travel to Chester Zoo for on-site data collection
- Applicants must hold or be close to completing a relevant PhD
Funding & terms
How to apply
Submit your CV and a detailed covering letter through the online application portal outlining your suitability for the role. Ensure a cover letter is included, as applications without one may not be considered at the shortlisting stage.
- CV
- Cover letter
Contact
Charlotte Brassey· Principal Investigator
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