349 data-"https:" "https:" "https:" "https:" "Simons Foundation" positions at Monash University
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ML predictions and their uncertainty to different stakeholders, and evaluate the effect of the conveyed information. The expected outcome of this project is an innovative conversational agent
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a scholarship has assisted me in relieving some of the financial pressures of study. Further, as a result of my scholarship, I have been able to purchase a new computer to assist in my studies
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of Computer Science in Data Science (Honours) Anban Raj Thank you will never suffice to express my gratitude to the Ng Family for believing in my potential and enabling me to access a world-class education. I will
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financial, personal, and confidential information. This project seeks to introduce machine learning and artificial intelligence techniques to effectively detect phishing websites. By leveraging these advanced
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Understanding factors related to student retention and experience in physics and astrophysics major units. Using quantitative (surveys) and qualitative data (interviews with students) this project
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Advisory System, or data from other implantable or wearable devices. This involves consideration of both feature-based machine learning or data science approaches and neural mass parameter estimation
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A recommender system is a subclass of information filtering/retrieval system that provides suggestions for items that are most pertinent to a particular user without an explicit query. Recommender
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explore unconventional ideas, develop computer algorithms for data analysis, create new experimental approaches, and apply the technique in areas like biomedicine, materials science, and geology. My group
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existing tokenization frameworks, analyzing potential risks, and developing novel security protocols to protect sensitive data and ensure the integrity of tokenized assets. Applicants will investigate
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the relevant faculty before beginning your application. For more information visit our website or contact our Graduate Research Admissions team on E: mgro-apply@monash.edu or T: +61 3 99051538