306 computer-programmer-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"Dip" positions at Monash University
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Performance Computing platform (MASSIVE) to do the experiments.
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into AI systems or mathematical and computational models of brain function. This project would be for someone who wishes to pursue a deeper understanding of humans and machines and the meaning this has
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This project explores the development of digital tools that measure the carbon footprint and nutritional impact of meals to support sustainable eating. It aims to integrate environmental and nutritional data into a user-friendly platform, enabling consumers, restaurants, and policymakers to make...
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* at a Monash campus in Australia: Bachelor of Engineering (Aerospace Engineering) Bachelor of Engineering (Electrical and Computer Systems Engineering) Bachelor of Engineering (Materials Engineering
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This Masters or PhD project 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 conveyed information. The...
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My area of expertise is condensed matter theory. I am interested in the interplay between interactions and unconventional electronic properties of novel materials including graphene, topological insulators and Weyl semimetals. The former favours quantum states of matter (e.g. excitonic...
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the area of end-to-end modular autonomous driving using computer vison and deep learning methods. This includes developing an efficient and interpretable image processing, vision-based perception and
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, containerisation (Docker), and basic bioinformatics pipelines will be preferred. Cross-disciplinary training and co-supervision with computational and neuroscience partners under GEMS 2026 will be provided. Project
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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. This improved my capacity to focus on my studies and
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for inference, yet differs from standard Bayesian approaches through its information-theoretic foundation. The MML87 approximation achieves computational tractability while remaining virtually identical to Strict