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responsible for the supervision of ~150 PhD students, reflecting research strengths and expertise in the disciplines of Zoology, Computational Biology, Conservation Biology, Ecology, Evolutionary Biology
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responsible for the supervision of ~150 PhD students, reflecting research strengths and expertise in the disciplines of Zoology, Computational Biology, Conservation Biology, Ecology, Evolutionary Biology
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Environmental Engineering Mechanical and Aerospace Engineering Electrical and Computer Systems Engineering Chemical and Biological Engineering Materials Science and Engineering About the Role We are seeking
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external organisations. Applicants from a range of disciplines or fields will be considered, including electrical, electronics, computer systems or telecommunications engineering. If you're curious about
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right-hand side of this page Please note that this link will direct you to the general "Equity Scholarship Program " application form. Once you submit your application, you will then be considered for all
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limited to the malfunction of any computer, cable, network, hardware, or software, or other mechanical equipment; (c) the unavailability or inaccessibility of any transmissions, telephone, or internet
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and Computer Systems Engineering ● Materials Science and Engineering ● Mechanical and Aerospace Engineering To be eligible to apply for domestic postgraduate research scholarships an applicant must be
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Employment Type: Full Time Permanent Remuneration: $113926 + 17% super (level 7) Location: Kensington UNSW Campus (hybrid) Why Your Role Matters The Change and Training Analyst (Student Systems) supports the effective adoption and ongoing use of student systems through training, communication,...
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This PhD project is funded by a successful ARC Discovery Project grant: "Improving human reasoning with causal Bayesian networks: a user-centric, multimodal, interactive approach" and the successful applicant will work as part of a larger research team. Reasoning and decision making under...
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Anomaly detection is an important task in data mining. Traditionally most of the anomaly detection algorithms have been designed for ‘static’ datasets, in which all the observations are available at one time. In non-stationary environments on the other hand, the same algorithms cannot be applied...