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sensor data, including LIDAR and camera inputs, for robotics and automation applications. Conduct outdoor vehicle trials for testing and validation of perception, navigation algorithms, and self-driving
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experience applying algorithms to solve problems in areas like NLP, Computer Vision, or on tabular data. Generative AI & LLMs: Hands-on experience developing LLM-powered applications, including Prompt
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new quantum algorithmic solutions based on Riemannian geometry. With whom? With Prof. Marek Gluza at NTU Singapore who is eager to debate with you whether double-bracket quantum algorithms or a
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, including BIM-based SLAM, traversability map analysis, and 3D LiDAR/vision sensor fusion. • Design few-shot learning algorithms for robust detection of temporary construction objects and obstacles
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. The successful candidate will assist in developing novel algorithms and integrating them into robotic platforms, helping to push the boundaries of embodied intelligence in both research and practical deployment
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. The successful candidate will assist in developing novel algorithms and integrating them into robotic platforms, helping to push the boundaries of embodied intelligence in both research and practical deployment
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developing quantitative evaluation methodologies or performance metrics. Strong programming skills in Python and modern AI frameworks (e.g., PyTorch, Hugging Face). Experience with optimization algorithms
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. Understanding of navigation framework and path optimization algorithms. 4. Proven track record of peer-reviewed publications. Appointed candidates will support research planning and execution, including
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to support reliable DAS interpretation and urban infrastructure monitoring. Key Responsibilities: Develop automated, uncertainty-aware algorithms to infer and map fiber-optic cable routes from DAS-derived
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ingestion and the RAG-based LLM reasoning engine. Key responsibilities include designing the algorithms, collaborating closely with multidisciplinary teams, and leading groups of student interns.