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Field
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, computational imaging as well as computer vision applications Key Responsibilities: The roles of this position include: Research on the cutting-edge AI algorithms for processing and modeling high-dimensional data
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of causal reasoning tools, including causal inference, counterfactual analysis, causal discovery. Development of deep learning methods on computer vision. Job Requirements: Preferably PhD in Computer
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disciplines, including human-robot interaction, robot learning, soft robotics, computer vision, and agricultural robotics. About the PhD project: We are looking for a highly motivated and talented PhD research
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undergraduate students. Criteria of the candidate: PhD in the field of wireless communication, computer science, or any related field. Strong publication record in high-impact conferences/journals. Aptitude
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: Autonomous Systems and robotic platforms Agricultural Robotics and precision agriculture technologies Artificial Intelligence and Machine Learning applications Computer Vision and sensor integration
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coverage effective on your very first day 2:1 Match on retirement savings Responsibilities* Working alongside with wet-bench scientists and PhD candidate (both with and without computational experience
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, dental, vision, prescription) Flexible spending accounts & wellness programs Professional development & mentorship opportunities To learn more about why UC is a great place to work, please visit our
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PRIMARY DETAIL - Salary Package: $109,272 (Level A, Step 6 - PhD awarded rate) p.a., plus 17% employer's superannuation and annual leave loading - Appointment Type: Full-time (35 hours per week
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Number: 6480973 Postdoctoral Research Fellow About the Opportunity Job Summary The department of Electrical and Computer Engineering and Institute for the Wireless Internet of Things (WIoT) is seeking a
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, computational imaging as well as computer vision applications Key Responsibilities: The roles of this position include: Research on the cutting-edge AI algorithms for processing and modeling high-dimensional data