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expertise in discrete choice modelling, statistical modeling, traffic simulation, machine learning, and optimization techniques. • Strong expertise in discrete choice modelling, statistical modelling, and
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geophysical survey and machine learning algorithms. Mainly responsible for processing geophysical/geomechanical data and analysing the data using machine learning. Conducting research, supervising undergraduate
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Job Summary: The Research Fellow will be responsible for undertaking in-depth research and innovation in machine learning, data science, and artificial intelligence on a novel urban intelligence
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-UAS technologies o Multi-agent systems and swarm robotics o Autonomous navigation and guidance o Computer vision and perception o Machine learning
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lab experiments Publish results in top-tier journals in related fields Assist in mentoring PhD students Job Requirements: PhD degree in mathematics, systems engineering, or machine learning Expertise in
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the supervision of the Principal Investigator, including but not limited to the following: Develop new computational tools through the application of AI / deep learning / machine learning / statistics on spatial
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areas of environmental change, remote sensing, infectious disease surveillance, spatial epidemiology, machine learning and global health. Key responsibilities: - Conduct high quality research in
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geophysical investigation, geomechanical engineering, and machine learning. The Centre for Urban Solutions is to provide leadership in developing innovative solutions and sustainable technologies for space
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will focus on efficient probabilistic analysis of high-dimensional and dynamic systems, including advanced sampling, surrogate modelling, and AI or machine-learning methods where appropriate. Key
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Intelligence & Machine Learning Develop machine learning and AI models to identify, predict and characterise genome instability patterns. Design generative and predictive computational models to infer mutational