Computer Vision Lecturer / Specialist
Job Overview
We are seeking a highly skilled and innovative Computer Vision Lecturer to join our faculty. You will be responsible for guiding students through the sophisticated world of machine perception—teaching them how to build systems that can interpret, analyze, and understand visual data from the world. Your goal is to translate complex geometric and deep learning concepts into actionable engineering skills, preparing the next generation of experts to push boundaries in autonomous systems, medical imaging, and augmented reality.

Job Responsibilities
Instructional Delivery: Lead comprehensive courses on fundamental and advanced Computer Vision topics, including image processing, feature detection, object recognition, image segmentation, 3D vision, and video analysis.

Curriculum Development: Architect a rigorous curriculum that balances foundational mathematics (linear algebra, projective geometry, signal processing) with modern deep learning-based approaches (CNNs, Transformers for Vision, GANs, Diffusion Models).

Hands-on Lab Management: Oversee coding laboratories where students design and implement vision pipelines using industry-standard libraries like OpenCV, PyTorch/TensorFlow, and Scikit-Image, working with real-world image/video datasets.

Research & Mentorship: Lead original research in areas such as visual understanding, robotic vision, or generative models. Mentor students through final-year capstone projects and research theses.

Assessment & Project Oversight: Design assessments that emphasize technical implementation—such as building real-time object detection systems or image-restoration pipelines—testing both coding rigor and algorithmic understanding.

Ethics & Society: Integrate critical discussions on surveillance, privacy, algorithmic fairness in vision systems, and the societal impact of automated image recognition.

Industry & Lab Partnership: Facilitate collaboration with research labs and tech companies to keep the curriculum aligned with cutting-edge advancements (e.g., edge vision, real-time inferencing).

Job Requirements
Education: PhD in Computer Science, Electrical Engineering, or a related field (focusing on Computer Vision/AI) is highly preferred.

Experience: Demonstrated experience in computer vision research or applied engineering, combined with a passion for academic instruction.

Technical Skills:

Core Math: Strong command of linear algebra, probability, and geometry.

Frameworks: Mastery of at least one major DL framework (PyTorch is strongly preferred) and experience with OpenCV.

Performance: Understanding of image acquisition, sensor physics, and performance optimization for real-time vision applications.

Soft Skills:

Visual Intuition: An exceptional ability to explain high-dimensional data, feature spaces, and latent representations in intuitive, visual ways.

Problem-Solving: A research-driven, methodical approach to troubleshooting vision models (e.g., addressing lighting variations, occlusion, or domain shift).

Continuous Learning: A relentless drive to stay ahead of the rapidly changing literature in the computer vision field.

Collaboration: Aptitude for interdisciplinary work, as computer vision often intersects with robotics, health, and design.

Benefits
Competitive Compensation: Attractive salary package with opportunities for research grants and industry consulting.

Advanced Resources: Access to GPU compute clusters, high-quality cameras, robotic sensors, and professional-grade datasets.

Scholarly Freedom: Support for attending top-tier global AI/Vision conferences (e.g., CVPR, ICCV), publishing research, and sabbatical opportunities.

Comprehensive Benefits: Full insurance coverage, academic leave, and retirement benefits in accordance with local labor laws.

Career Growth: Clearly defined paths toward Tenured Professor, Research Lab Director, or lead R&D roles in private industry.

Computer Vision Lecturer, AI/Vision Professor, Research Scientist (Vision), Computer Vision Engineer (Education focus), Faculty in Visual Intelligence.

Industry Keywords: Image Processing, Object Detection, Segmentation, 3D Reconstruction, Transformers, OpenCV, PyTorch, Real-time Inferencing, Machine Perception.

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