123 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" positions in Singapore
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, Biostatistics, Statistics, Bioinformatics, Computational Biology, or other AI-related disciplines. Strong foundation in AI, statistical modeling, machine learning, or high-dimensional data analysis. Proficiency
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of wireless communications, signal processing and machine learning methods and algorithms for urban anomaly detection and human activity classification through 5G signal recording, processing analysis
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workflows for processor and accelerator design, verification, and physical implementation using open-source tools. Explore architecture-algorithm co-design for machine learning and AI acceleration. Perform
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third largest university by intake in Singapore. SIT’s mission is to innovate with industry, through an integrated applied learning and research approach, so as to contribute to the economy and society
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learning and development Proficient in technical writing and presentation Possess strong analytical and critical thinking skills Show strong initiative and take ownership of work Where to apply Website https
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accelerator design, verification, and physical implementation using open-source tools. Explore architecture-algorithm co-design for machine learning and AI acceleration. Perform performance, power, and area
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enablement Leverage data and emerging technology (e.g., Power BI, Robotic Process Automation (RPA), Artificial Intelligence/Machine Learning (AI/ML)) to solve challenges and innovate FSS operations Stakeholder
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work environment Learn more about CQT at https://www.cqt.sg/ Job Description A postdoctoral research fellow position on the topic of quantum error correction is available in the group of Associate
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independently and as part of a team Experience with machine learning and AI applications in engineering is advantageous We regret to inform that only shortlisted candidates will be notified. Hiring Institution
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Intelligence, or a closely related discipline. Strong research background in AI and machine learning, with a focus on efficient or accelerated models. Proven experience with model compression techniques, such as