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the ranking. However, STV method becomes considerably more complex with encrypted ballots. Our goal is to develop an algorithm/protocol to count encrypted ballot using the STV method. Our first point of
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Approximation. Parameterized Complexity is a vastly growing area within theoretical computer science that allows for the development of exact and approximation algorithms for computationally hard problems by
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including language understanding, generation, explainability and reasoning, and dialogue systems. Efficient algorithm development for air traffic conflict resolution. Develop and evaluate AI models, including
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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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algorithms. The targeted starting date is 1 September 2025,or as soon as possible thereafter. Project description This project will explore the algorithms, advantages, and applications of quantum computing
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Learning Develop computer graphics and machine learning algorithms (e.g., SLAM and Gaussian Splatting), and evaluate their accuracy in scene reconstruction and camera trajectory estimation using videos
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Engineering, Computer Engineering, or Computer Science 2. Demonstrated, successful experience (academic or professional) programming in algorithm level languages such as Matlab/Simulink, Python, C# or similar 3
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package should be prioritised are surprisingly difficult computational tasks. State-of-the-art high-performance algorithms are used to calculate routes for the vehicles in order to minimise costs and
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friendly and international work environment Learn more about CQT at https://www.cqt.sg/ Job Description We are seeking a strong quantum computing researcher to develop quantum algorithms for generative
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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