384 computer-programmer-"St"-"Washington-University-in-St"-"St" positions at Monash University
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neurophysiological variable estimation framework we have been developing that can be applied to all kinds of brain activity recordings. There are two projects to be completed under this program and we are looking
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temporal data. See my time series research for more details of the research program on which this research will build. Required knowledge A solid grounding in machine learning Project funding Project based
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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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that are constructed in a way that is inspired by what we know about self-awareness circuits in the brain and the field of self-aware computing. The project will advanced state of the art AI for NLP or vision or both
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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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alumni, alumni cohorts, and key stakeholders, aligning with the University’s Alumni Engagement Plan and broader strategic goals. You will assist in creating alumni research snapshots, individual alumni
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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 to learn, and become a better
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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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, the position is essential to the smooth and timely delivery of research activities. Working with academic and clinical researchers, the Research Assistant will help plan and coordinate projects, prepare ethics
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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...