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Multiple Continuing (Tenure-Track) Academic Positions, School of Electrical and Computer Engineering
-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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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 3 months ago
expertise in one or more of a broad range of computational methods including but not limited to: machine learning / AI, spatial computing, computational creativity, text encoding, social media analysis
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-sensor hyperspectral data for crop disease detection and monitoring. Develop machine learning or physics-informed models to retrieve reliable spectral and/or biophysical features, from multi-scale
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, ticketing tools, web chat etc). Demonstrated ability in the use of a range of computer applications (Windows) and the ability to quickly learn new technologies. Desirable but not essential – Experience with
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societal applications: Computer Systems and Computing Infrastructures Cybersecurity and Trustworthy Digital Systems Machine Learning and Artificial Intelligence Robotics and Autonomous Systems All positions
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development. Familiarity with software development lifecycle including design and documentation of software architecture, testing/debugging skills, and version control. Experience applying machine learning
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based at other campuses of the University About the role As Assistive Technology Specialist, you will play a key role in supporting equitable access to learning and research by providing expert guidance
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student societies, and are actively involved in teaching and learning opportunities within the school. For further information about the School, please visit - https://www.unsw.edu.au/engineering/our
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Science and Machine Learning Cybersecurity Software Engineering Digital Health Computer Science Education To Apply Please submit your CV and covering letter addressing your suitability for this position
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materials systems at the molecular level with machine learning. The PhD Student will undertake a study analysing mass spectral imaging data streams in real time using machine learning workflows. A pathway for