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: enrol as a full-time, internal student have a bachelor degree with honours or a master degree (with a significant research component), in a discipline of relevance to the research topic knowledge
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reviewed publication/s, ideally as lead author experience applied quantitative skills to an environmental problem experience managing and analysing complex datasets knowledge or interest in complexity
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as a full-time, internal student have an honours or masters degree in one of these areas: robotics computer science other related discipline. How to apply Apply for this scholarship at the same time
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interest and knowledge of emerging technologies such as AI and robotics experience using and interpreting qualitative and quantitative research methods and tools (e.g. NVivo, SPSS, R) strong report and
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: an honours degree, Master of Philosophy degree or equivalent in applied mathematics, quantitative ecology, economics, engineering, or other relevant quantitative discipline. The desirable criteria
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. To address this gap in knowledge, the proposed project will seek to examine visitors, workers, and volunteers’ safety concerns, fear of crime and perceptions of victimisation risk at mass events (e.g
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external enrolment procedures. Ideally, you should have: an engineering degree, preferably chemical engineering with flow sheeting experience an interest in renewable energy and/or hydrogen an interest in
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Machine Learning for Image Classification. Eligibility You must: We would like you to have: sound knowledge of machine learning, computer vision and image processing strong programming skills. How to apply