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Field
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Architecture: Architect, build, and evaluate multi-agent systems powered by LLMs and machine learning, incorporating Orchestrator and Memory agents, vector databases, and knowledge graphs to enable complex goal
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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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Computer Engineering, Computer Science, Electronics Engineering or equivalent. Strong background in machine learning and computer vision. Strong publication records in top-tier machine learning or computer
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background in geomodelling, geophysical and geotechnical investigation, geomechanical engineering, and machine learning. You will be expected to work effectively on a geophysical/geomechanical project, to
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road safety analytics framework. The role involves integrating multi-source transport datasets, developing advanced analytical and machine learning models for risk identification, and supporting
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experience in, for example, machine learning, high-performance computing, reconfigurable hardware, cloud computing, compiler engineering, distributed systems, or DevOps are encouraged to apply, as
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MACQUARIE UNIVERSITY - SYDNEY AUSTRALIA | North Ryde, New South Wales | Australia | about 18 hours ago
differential geometry, algebraic geometry, etc.) or for computer science (such as machine learning, linear logic, etc.). While the position start date is flexible, the successful applicant must have completed
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Unit: Electrical and Computer Engineering Employee Category: Research Staff Location: Kent Ridge Campus Posted On: 27/07/2026 ▲ Collapse Job Title: Research Fellow (Speckle Dynamics and Transcranial
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such as Python and/or R, with experience analyzing large-scale molecular, clinical, or biomedical datasets. Experience developing or applying machine learning, statistical modeling, or artificial
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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