Senior AI Scientist - Wildlife 3D Vision & Conservation

Manchester Metropolitan University; Manchester; Hybrid; GBP 42,000 - 48,000; Full time

Job summary

Manchester Metropolitan University invites applications for a research role focused on AI-driven reconstruction of wildlife size and body condition from camera-trap images. You will develop monocular depth-estimation and 3D reconstruction methods, curate diverse datasets, and collaborate with Chester Zoo and the Max Planck Institute.

The role emphasizes exploring open-source tools, contributing to publications, and supporting Phase 2 funding through rigorous validation and dissemination.

Qualifications

• PhD (or near completion) in a quantitative/computational discipline (e.g., Computer Science, AI, ML, Robotics).
• Strong Python programming skills.
• Practical experience with deep-learning frameworks (PyTorch, TensorFlow or equivalent).
• Experience developing/adapting/evaluating computer-vision or ML models.
• Experience with quantitative analysis and rigorous evaluation of computational methods.
• Evidence of independent contribution to research projects.
• Excellent written and verbal communication; able to work in an interdisciplinary team.
• Willingness to travel to Chester Zoo for on-site data collection.

Responsibilities

• Benchmark and fine-tune monocular depth-estimation models using camera-trap imagery.
• Develop AI-based methods for single-image 3D reconstruction of animals and measure body dimensions in real-world units.
• Curate and manage colour, LiDAR, photogrammetry and 3D datasets.
• Develop reproducible computational pipelines using Python and deep-learning frameworks.
• Perform quantitative validation, statistical analysis and evaluation of model performance.

Skills

Python

Deep learning

Computer vision

Research experience

Communication

Teamwork

Travel to Chester Zoo

Education

PhD in Computer Science / AI / ML

Tools

PyTorch

TensorFlow

Job description

Manchester Metropolitan University invites applications for a research role focused on AI-driven reconstruction of wildlife size and body condition from camera-trap images. You will develop monocular depth-estimation and 3D reconstruction methods, curate diverse datasets, and collaborate with Chester Zoo and the Max Planck Institute.

The role emphasizes exploring open-source tools, contributing to publications, and supporting Phase 2 funding through rigorous validation and dissemination.