197 machine-learning-"https:"-"https:"-"https:"-"https:" positions at University of Sydney
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Full-time, continuing position Harness your expertise as Peer Learning Technologies Officer Base salary $89,755 + 17% superannuation About the opportunity The Peer Learning Technologies Officer
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with SCION in New Zealand bringing together researchers in robotic perception, machine learning, remote sensing and silviculture to transform and upscale forest phenotyping operations. The role will be
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-physical Systems Machine Learning and Artificial Intelligence Quantum Devices and Systems Robotics Security and Dependability Signal Processing Software Engineering All positions are full-time, continuing
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Fixed term, full time, two-year position. Located in the School of Electrical and Computer Engineering in J03 Office, Engineering Precinct, Darlington. Opportunity to provide education and
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an equivalent discipline) expertise in statistical and machine learning approaches, with the ability to apply advanced methods to complex environmental and agricultural datasets proficiency in R and/or
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opportunity In this opportunity as a Senior Clinical Simulation Specialist, you will collaborate with academic staff to develop and implement clinical simulation scenarios that align with the program’s learning
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: Using big data insights to optimise the manufacturing process The second phase of this project will focus on processing and utilising machine-learning techniques to analyse large volumes of data from
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intelligence, machine learning, automation, robotics, natural language processing, quantum computing, DevOps uplift and next-generation digital platforms. Enterprise Architecture is an equally critical component
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such as Power BI, Excel, and PowerPoint for diverse audiences. Employ advanced analytics techniques, including machine learning, to forecast trends and support data-driven decisions. Collaborate across
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funded under the Commonwealth Department of Health’s Rural Health Multidisciplinary Training (RHMT) Program. Our focus at the BHUDRH, is to lead the design and delivery of innovative teaching and learning