444 web-programmer-developer-"https:"-"https:"-"https:"-"https:"-"https:" positions at Monash University
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IBL program . Number offered Two scholarships available. Selection criteria Awarded based on need. To retain this scholarship: You must maintain a Weighted Average Mark (WAM) of 50 each semester. How
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for a place in Monash Minds, a full-funded leadership program for Indigenous first-year students. Number offered One scholarship available. Selection criteria Awarded based on need. To retain
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financial hardship . Benefits $6000 per annum (48 credit points of study) until the minimum points for your degree are completed. An invitation to apply for a place in Monash Minds , a leadership program for
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to dedicate more time to my studies as well as to other things to promote my leadership skills, such as through the Access Monash mentoring program. This opportunity has only helped encourage my passion
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the power of LLMs to develop advanced computational methods for the detection and mitigation of misinformation and disinformation. More specific objectives are: To investigate the effectiveness of large
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initiatives. As the successful candidate, you will be responsible for: Leading the development and delivery of strategic HR Business Partnering services aligned to University and portfolio priorities. Coaching
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Monash Rural Health, overseeing budgets, external funding programs and financial reporting. This includes supporting major funding initiatives such as the Rural Health Multidisciplinary Training Program
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, yielding negligible performance gains or even inducing catastrophic forgetting. To bridge the gap between theoretical AL and real-world deployment, this PhD project will develop resilient active learning
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Grace Kang Global Assist Grant The Grace Kang Global Assist Grant is introduced to support coursework students who participate in an overseas study program as part of their Monash degree. Total
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these issues is critical for building trustworthy multimodal AI systems. Research Objectives The goal of this PhD project is to develop scalable Bayesian uncertainty estimation frameworks for single- and multi