408 machining-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" positions in Singapore
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To support the day-to-day technical operations of the Electrical Machines & Drives Laboratory (EMDL), ensuring safe and efficient running of high-power electrical equipment, facilitating
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Job Description Job Alerts Link Apply now Research Engineer (MEMS Fabrication & Piezoelectric; Sensors; Machine Learning & Neural Networks) ▲ Collapse Job Title: Research Engineer (MEMS Fabrication
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Job Description Job Alerts Link Apply now Research Assistant (Computational Science and Machine Learning) University-Level Unit: College of Design and Engineering Faculty/Department-Level Unit
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We invite excellent candidates in classical machine learning to join a collaborative research initiative between the MathEXLab of NUS (Mechanical Engineering) and the Centre for Quantum Technologies
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development and strategic initiatives. Job Requirements: Ph.D. in Artificial Intelligence, Computer Science, Machine Learning, Natural Language Processing, Information Retrieval, Data Science, or a closely
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are met on time. Job Requirements: Bachelor's degree in Computer Science, Computer Engineering, Mathematics, or a related field. Good knowledge of computer security. Experience in computer science research
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the PI and research team. Job Requirements: Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field. Good knowledge of computer networks and network security
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• PhD in Chemistry, Materials Science, Chemical Engineering, Physics, or a related discipline. • Strong experimental research skills with a good publication record. • Experience in advanced materials synthesis, characterisation, and device fabrication. • Familiarity with...
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• B.S. or M.S degree in a relevant area, e.g., Chemical Engineering, Control Engineering, Computer Science, Chemistry, etc. • Experienced in machine learning, optimization and programming
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for Science, and scientific discovery by advancing our understanding of interpretable machine learning models and their practical applications in real-world domains such as healthcare and science. Key