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packages and a track record of delivery on project-based work. To be successful at Level HEO8 you will need: Have excellent and extensive industry experience in computer science, data science or (applied
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the direction of A/Prof Claudia Szabo in the School of Computer and Mathematical Sciences at the University of Adelaide. This position will work with our partners Praetorian Aeronautics and their testing team
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demonstrate suitable experience in computer science, machine learning, robotic vision, or a related field (through a high-quality Honours or Masters degree). The successful candidate must be able to enrol as a
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Educational Technology in the School of Computer and Mathematical Sciences. The successful candidate will be a researcher in the use of technology to support cognitive and meta-cognitive skills of students
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Project Part B in Trimester 1, 2026 Master of Computer Science - semester 2, 2025 enrolment in: COMP SCI 7100A - Research Project Master Computer Science Part A Masters of Mathematical Sciences - semester 2
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in accordance with PSBA’s standards. You will lead the nodes lifecycle management program for biotechnology derived plants and plant products. The Faculty of Sciences, Engineering and Technology (SET
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-performance computing (HPC), Bragg Crystallography facility, and Adelaide Proteomics Centre. Our collaboration with Monash University further extends our access to advanced 300 kV Titan Krios and Helios 5 UX
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contribution of 17% superannuation applies. 24 Months Fixed term Part time position until Oct 2027. This postdoctoral position in computational cognitive science and data science offers an exciting opportunity
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program (PhD or MPhil) at the University of Adelaide in one of the eligible disciplines listed above; Undertaking research aligned with the fields of mineral processing, mining engineering or chemical
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methods for provable network security. The School of Computer and Mathematical Sciences is recruiting a research fellow to work on next generation network security technologies. Join a world-class research