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university research into commercial outcomes. Under this program, PhD students will gain unique skills to focus on impact-driven research. This Project aims to develop a predictive machine learning model
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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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deep learning. The purpose of this scholarship is to support a PhD student to contribute to the advancement of infrastructure monitoring technologies with strong industry collaboration. Student type
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demonstrated ability to communicate and interact with a diverse range of stakeholders and students. Demonstrated knowledge in Quasi-Monte Carlo methods and/or finite element analysis and/or machine learning is
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educator with a PhD in Science or Mathematics Education, bringing expertise in teaching and research across the primary and middle years of schooling. With a passion for curriculum innovation and student
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at the Australian National University. The Fellow will lead independent, high-impact research in advanced machine learning and hybrid modelling for genomics and cellular processes, contributing directly to the
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group of PhD researchers who will tackle the most pressing questions in Machine Learning while ensuring AI serves humanity responsibly. You'll work within one of our specialised research themes, each
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. The candidate will work closely with the CIs, post doc and PhD (machine learning) candidate, to develop choreographic structures used to generate movement and interaction capabilities that will define human-robot
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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
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external enrolment procedures. Selection criteria Demonstrated experience in programming and system development. Expertise in Python programming and data analysis. Experience developing Machine Learning