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and strategies at an institute of higher learning. Strong working knowledge around pedagogy, data science, software design, machine learning, AI, cybersecurity, data and AI governance framework
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Electrical and Electronic Engineering, or related field. Research experience with Artificial Intelligence/Machine Learning/Large Language Model. Publication track record in a series of top tier conference
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undergraduate and postgraduate modules in areas such as: • Fundamentals of Robotics • Control Systems and Mechatronics • AI and Machine Learning for Robotics • Embedded Systems and Intelligent Sensors
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). Applying advanced statistical and machine learning methods (e.g., predictive modelling, clustering, multivariate integration) to large-scale time series and sensor datasets. Contributing to the development
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/ machine learning algorithms to support research in the IDMxS Analytics Cluster. The RF will apply/ improve machine learning algorithms to process (e.g., classify, predict) data collected by IDMxS. Help
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work environment Learn more about CQT at www.quantumlah.or Roles & Responsibilities Administrate CQT PhD students candidature milestones (eg. QEI, QE II, Progress Report, Oral Defence etc) Administrate
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international work environment Learn more about CQT at www.quantumlah.or Roles & Responsibilities Administrate CQT PhD students candidature milestones (eg. QEI, QE II, Progress Report, Oral Defence etc
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, machine learning, and life cycle assessment, we aim to create sustainable wearable systems to enhance human well-being. For more details, please view https://www.ntu.edu.sg/mse/research . We are looking
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++. Demonstrable experience with machine learning frameworks (e.g., PyTorch, TensorFlow). Hands-on experience with simulation environments such as Unity ML-Agents, NVIDIA Isaac Sim, Mujoco, or similar. Solid
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novel research methodologies in computer vision, deep learning architectures, and neuro-fuzzy systems to contribute to the development of robust AI frameworks for medical diagnosis and treatment support