667 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" positions at Nanyang Technological University in Singapore
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research in Physics-Informed Machine Learning (PIML) for metal additive manufacturing process. This role will focus on developing novel machine learning frameworks that seamlessly integrate physical
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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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A Machine Learning Engineer position is currently available at NTU and the start-up TT-logic, part of the incubator NTUitive from the Nanyang Technological University. The candidate is expected
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The Senior Executive, Learning Systems & Tech and Course Registration is responsible for end-to-end academic administration and digital learning support to ensure accurate, compliant, and seamless
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advance research in computer vision, machine learning, and/or robotics for the digitalization, monitoring, and automation of civil infrastructure. The role will focus on developing innovative methodologies
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background in earthquake monitoring. The successful candidate will lead and contribute to developing a machine-learning powered earthquake monitoring and early warning system. The role involves both
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. Develop AI and machine learning models for recycling process prediction and decision support, such as forecasting metal recovery, impurity levels, energy use, and emissions. Develop optimization and control
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journals and conferences Good research experience in AI and machine learning as well as wireless networking Independent, highly analytical, proactive and a team player Excellent teamwork and verbal, written
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computational chemistry, reaction network analysis, and machine learning for organometallic catalytic reactions. 2. Design of membrane-permeable macrocyclic peptide drugs via machine learning structure
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/Research Fellow(SRF/RF) to carry out research in robotics and machine learning by exploring cutting-edge approaches such as learning-based robot perception, adaptive control with reinforcement learning