Research Assistant in AI-based Image Analysis
Core
Develop, train, and validate deep learning models for automated detection and classification of marine species from underwater imagery and video datasets.
Role type
Research Assistant in AI-based Image Analysis
Builds
Deep learning models and computer vision pipelines for marine biodiversity monitoring
Domain
Marine ecology / Computer Vision / AI
Deliverable
production ML models
Required skills
Deep learning frameworks (PyTorch, TensorFlow), Python programming, Computer vision, Image/video analysis, Experimental design, Quantitative evaluation, Scientific writing
Preferred skills
Object detection/segmentation models (YOLO, Mask R-CNN), Large dataset annotation tools (CVAT), Linux environments, Data augmentation, Transfer learning, Environmental monitoring experience
Technologies
PyTorch, TensorFlow, Python, CVAT, Git
Responsibilities
Curate and preprocess underwater imagery/video datasets; Design and evaluate deep learning models for species detection; Develop computer vision pipelines for video processing; Evaluate model performance using quantitative metrics; Integrate AI models into operational monitoring workflows; Collaborate on project reports and dissemination materials
Seniority
Mid-level Researcher (3+ years experience)
