202 machine-learning "https:" "https:" "https:" "https:" "https:" "The University of Edinburgh" positions at SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
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Science, or a related technical field Master's or PhD degree in Machine Learning, Computer Vision, or related areas will be advantageous Preferred Qualifications: Experience with biological/ecological
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learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI
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by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Role Overview As a University of Applied Learning, SIT works closely with industry in our
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Science, or a related technical field Master's or PhD degree in Machine Learning, Computer Vision, or related areas will be advantageous Preferred Qualifications: Experience with biological/ecological
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Role Overview As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have opportunities to tackle real-world, industry-relevant
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++. Demonstrable experience with machine learning frameworks (e.g., PyTorch, TensorFlow). Hands-on experience with game AI agents and/or GUI agents such as Mineflayer, Unity ML-Agents, or similar. Solid expertise in
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The Singapore Institute of Technology (SIT) is Singapore’s first University of Applied Learning and the third largest university by intake in Singapore. Our mission is to maximise the potential
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the Job related to staff position within a Research Infrastructure? No Offer Description Introduction As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our
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to staff position within a Research Infrastructure? No Offer Description As a University of Applied Learning, the Singapore Institute of Technology (SIT) works closely with industry in its research
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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