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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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Job Description Job Alerts Link Apply now Job Title: Research Fellow (Genome Editing - Directed Evolution) Posting Start Date: 16/04/2025 Job Description: Job Description We are seeking a talented
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, quantum machine learning, quantum algorithms from well-established universities/institutes. The candidates must be highly motivated in multidisciplinary research. He/she must have proven experience in
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of Singapore’s maritime sector. The project focuses on developing planning methods to support the electrification of harbour craft fleets, using real-world operational data to derive charging demand profiles and
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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on AI-driven end-to-end autonomous driving algorithms. Key Responsibilities: The research fellow will be leading the development of AI-driven end-to-end autonomous driving algorithms. The work will
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) Design robust obstacle avoidance algorithms for mobile robots in dynamically changing environments, focusing on formal safety constraints and real-time performance in unpredictable conditions. b) Develop
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of this role is to support and contribute to an industry innovation research project. The Research Engineer will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep
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of performance, speed, and precision. Key Responsibilities: Design and implement genAI models for embodied AI systems. Develop and optimize deep learning algorithms to enable robotic arms to perform complex tasks