20 computer-vision Fellowship positions at SINGAPORE INSTITUTE OF TECHNOLOGY (SIT) in engineering
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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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with direct industrial impact. Responsibilities The successful candidate will: Conduct cutting-edge research in Computer Vision, Video Understanding, and Multimodal AI. Design AI models for concept
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assigned by Supervisor. Requirements PhD in Computer Science or related field Expertise in computer vision and vision-language models Experience with ML evaluation metrics and benchmarking Proficiency in
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Vision, Video Understanding, and Multimodal AI. Design AI models for concept-driven video understanding of consumer facial care behaviours. Work with PI and company to develop the AI solution Develop novel
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for: Conducting research and development on AI-based solutions for automated defect inspection and condition assessment of train components by designing and developing deep learning, computer vision, and machine
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(Kubernetes), serverless computing, and REST API development. Proficient in Python, with basic experience in machine learning or computer vision libraries; familiarity with Vision-Language Models (e.g., CLIP
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learning or computer vision libraries; familiarity with Vision-Language Models (e.g., CLIP, BLIP) or scene-graph inference is a plus. Key Competencies Strong software development and debugging skills. Able
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, or similar. Solid expertise in computer vision techniques, transformer architectures, and multi-modal learning. Familiarity with reinforcement learning (RL) principles, curriculum learning strategies, and the
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computer vision and vision-language models Experience with ML evaluation metrics and benchmarking Proficiency in Python and deep learning frameworks (e.g., PyTorch) Interest in applied, industry
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). Hands-on experience with game AI agents and/or GUI agents such as Mineflayer, Unity ML-Agents, or similar. Solid expertise in computer vision techniques, transformer architectures, and multi-modal