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Primary supervisor Thanh Thi Nguyen Research area Machine Learning Deepfakes, derived from "deep learning" and "fake," involve techniques that merge the face images of a target person with a video of a different source person. This process creates videos where the target person appears to be...
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intelligence techniques to effectively detect phishing websites. By leveraging these advanced methods, the goal is to enhance the ability to identify and mitigate the risks posed by fraudulent online platforms
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Skip to content Intelligent edge computing for adaptive demand response management: a distributed multi-agent approach (CSIRO Industry PhD Scholarship) Future student scholarship The CSIRO Industry
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interaction, or numerical simulation of marine or floating systems, with a focus on applying these methods to design and performance optimisation of engineered composite structures • High level of
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knowledge Interest in Interdisciplinary Work, strong mathematical background, reasonable coding skills, preferably experience with scientific computation, numerical methods. Project funding Other Learn more about minimum entry requirements .
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involve a lot of experiments using DL/AI <b>methods</b>. We will use the Monash High Performance <b>Computing</b> platform (MASSIVE) to do the experiments. Required knowledge You must have experience in Deep Learning, and have strong programming skills. Learn more about minimum entry...
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[Malaysia Campus- VPSSP] An AI-Informed Planetary Health Framework for Equitable AMR Risk Mitigation
modelling from Project 1, we will conduct focus groups and interviews with communities in high- and low-risk zones to capture local knowledge, behaviours, and risk perceptions related to AMR. In parallel
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education, pursuing their own research project during the mobility period, parallel to joining a research group and having a host supervisor at Lund University. For information about eligibility and selection
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angle, this project aims to build self-aware neural networks 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
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angle, this project aims to build self-aware neural networks 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