Description
Key Skills: OpenCV, C++, Python, TensorFlow, PyTorch, Machine Learning, Deep Learning, Image Processing, Computer Vision, AI/ML
Good to Have Skills: Experience with U-Net, Mask R-CNN, YOLO, Faster R-CNN, DETR frameworks. Knowledge of image enhancement and restoration techniques, noise reduction and filtering, morphological image processing, object detection and tracking, quantitative image analysis, image segmentation and classification. Experience with biological image segmentation, cell counting, cell tracking, morphology analysis, and biomarker quantification. Familiarity with generative AI, foundation vision models, and multimodal AI applications in scientific imaging.
Roles & Responsibilities:
- Lead the design, development, optimization, and validation of advanced image processing algorithms for scientific and biomedical imaging applications.
- Architect robust image analysis pipelines involving image enhancement, restoration, segmentation, registration, feature extraction, object detection, tracking, and quantitative image analysis.
- Drive development of scalable computer vision solutions using classical image processing techniques as well as AI/ML-based approaches.
- Evaluate and improve algorithm accuracy, robustness, computational efficiency, and scalability across large image datasets.
- Collaborate with scientists and domain experts to translate biological and scientific workflows into image processing and AI-driven solutions.
- Establish best practices for algorithm benchmarking, validation, performance testing, and reproducibility.
- Lead technical investigations and proof-of-concepts for emerging computer vision and AI technologies.
- Provide technical guidance and mentorship to engineers working on image processing and machine learning solutions.
- Design and develop machine learning and deep learning models for image classification, segmentation, object detection, anomaly detection, and predictive analytics.
- Lead model training, validation, deployment, and continuous improvement activities.
- Drive integration of deep learning models with traditional image processing workflows to deliver optimal product performance.
Experience Required: 7+ years of experience
Education: Master's degree