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David Shugg Professionalism Scholarship Industry Leaders Scholarship This Scholarship is to honour the important role that David Shugg played in the professionalism of paramedics. Throughout David’s career, he advanced and embedded professionalism in paramedic training and education in the...
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This PhD project is part of a larger project that aims to explain the uncertainty of Machine Learning (ML) predictions. To this effect, we must quantify uncertainty, devise algorithms that explain ML predictions and their uncertainty to different stakeholders, and evaluate the effect of the...
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Monash University-Pakistan Higher Education Commission (HEC) Joint Scholarship This joint scholarship program enables high-achieving Pakistani students to undertake PhD and research degrees here
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result of my scholarship, I have been able to purchase a new computer to assist in my studies. This improved my capacity to focus on my studies and achieve my academic goals. Law has been a dream of mine
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Awarded on performance at an interview. To retain this scholarship: You must maintain enrolment in a Monash University undergraduate degree and fulfil the requirements of the Peer Mentoring program to
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The United Nations Development Programme has identified access to information as an essential element to support poverty eradication. People living in poverty are often unable to access information
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computer science. Although the efficiency of the state-of-the-art decision and optimisation procedures hinges on a wealth of sophisticated heuristic mechanisms, the key part driving their exceptional practical
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on outstanding academic achievement and financial disadvantage. Students will be assessed on their personal aspiration statement and financial support statement and interview performance. To retain
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Scholarship My journey has been shaped by numerous challenges. I left home at 12 and grew up in the out-of-home care system, which had a significant impact on my academic performance and aspirations. Although I
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biodiversity and sustainability research. The initial objective is to use deep learning techniques to perform acoustic species identification in real-time on low-cost sensing devices coupled to cloud-based