76 security-"https:"-"https:"-"https:"-"https:"-"CUBO" positions at Monash University in Australia
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securing external funding, and proven capability in coordinating courses and supervising postgraduate researchers, supported by a strong commitment to collegial and scholarly engagement. About Monash
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the workplace, affecting workers’ mental health, financial security, family relationships, and children’s long-term outcomes. Yet, despite the rising frequency of economic shocks – from natural disasters and
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administration and stakeholder engagement, and will contribute to meetings, events and general program operations. This position will coordinate projects, streamline workflows and maintain accurate and secure
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strong publication record, success in securing external research funding, and experience in supervising postgraduate research students. For a Level D appointment, you will show distinction in research
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in International Trade Law, Taxation Law, or Technology Law. You will demonstrate success in securing external research funding, along with proven experience supervising postgraduate research students
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and securing high-impact coverage across print, digital and broadcast. Strong operational chops: resource planning, workflow management, and delivery against tight deadlines. Expertise in policy
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, conferences, or equivalent textbooks/teaching resources Ability to lead outstanding research and manage a research team and projects Proven success in securing significant external research grants Strong
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commitment to impactful research, and for more senior candidates, success in leading research projects, securing external funding, and supervising postgraduate students. About Monash University At Monash
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support systems in the ecosystem and food security domains. It explores the use of BNs and DSSs as a data source, and (semi-)structured expert judgement (SEJ) and knowledge elicitation to assess
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. Leveraging techniques such as federated learning, differential privacy, and secure multiparty computation, the goal is to enable collaborative ML tasks without compromising the privacy of individual data