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objects and segmentation models for a robotic pick and place project. Develop data augmentation/data synthesis methods to address challenges from limited training data. Develop algorithms to annotate 2D
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/ machine learning algorithms to support research in the IDMxS Analytics Cluster. The RF will apply/ improve machine learning algorithms to process (e.g., classify, predict) data collected by IDMxS. Help
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Centre for Advanced Robotics Technology Innovation (CARTIN) is looking for a candidate to join them as a Research Fellow. Key Responsibilities: Develop novel algorithms for multi-agent inverse
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” wherein messages including emotions are incorporated into the movements of collaborative robots. Key Responsibilities: Design, implement, and test real-time multi-objective motion planning algorithms
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ICs. Development cycle including circuit design, simulation, modeling, layout, verification and measurements Design high power-efficiency RF power amplifiers Develop scripts and algorithms for analog IC
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(terrestrial and NTN). The goal of this research is to design and develop algorithms and techniques that adapt to the environment, minimizing signaling overhead associated with channel estimation and enhancing
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-making algorithm for autonomous vehicles. The work will involve sensor fusion, perception, trajectory prediction and test rig set-up, and experimental validation. Job Requirements: PhD Degree in Vehicle
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. The roles of this position include: Development of algorithms to improve memory/sample/time efficiency of LLM training. Development of a workable prototype system with capabilities such as conversational
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Officer will be mainly responsible to process geophysical data and analyze the data using machine learning algorithms. The position involves in conducting research, supervising undergraduate students, and
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understanding of machine learning/deep learning fundamentals. Able to appreciate and explain the mathematical workings of common algorithms for computer vision/NLP/tabular data. Hands-on skills in Python-based AI