772 machine-learning-"https:"-"https:"-"https:"-"https:"-"RAEGE-Az" positions in Singapore
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in the 2025 QS World University Rankings by Subjects. We are hiring a Research Fellow in Signal Processing and Machine Learning to develop signal processing and machine learning algorithms and methods
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Requirements: A Ph.D. degree in a related discipline (transportation engineering, computer engineering/science, or related disciplines) by December 2025. Expertise in AI, deep learning, and programming (e.g
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Job Description Apply now Job Title: Senior Executive/ Assistant Manager, Learning Support Posting Start Date: 05/12/2025 Job Description: Job Description ... Qualifications ... More Information
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, and innovators to thrive in the digital age. Located in the heart of Asia, NTU’s College of Computing and Data Science is an ‘exciting place to learn and grow. We welcome you to join our community
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for drone swarms. The role will focus on multi-agent visual perception techniques. Group website: https://personal.ntu.edu.sg/wptay/ Key Responsibilities: Develop signal processing and machine learning
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The National Institute of Education invites suitable applications for the position of Research Assistant on a 24-month contract at the Science of Learning in Education Centre . Project Title
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discipline (e.g., computer science, data science, software engineering) Proficient in Machine Learning, Deep Learning, Python, Data Science, and AI/ML Toolkits Preferred Applicants with Master’s or PhD Degree
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teamwork and verbal, written communication skills In-depth knowledge of computer vision and deep learning Demonstrated capability to conduct innovative research We regret that only shortlisted candidates
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, and innovators to thrive in the digital age. Located in the heart of Asia, NTU’s College of Computing and Data Science is an ‘exciting place to learn and grow. We welcome you to join our community
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programming skills in Python and familiarity with AI/ML frameworks. Good understanding of LLM architectures, transformer models, and machine learning fundamentals. Experience with model serving / inference