364 computer-programmer-"https:"-"Prof"-"https:"-"https:"-"https:"-"https:"-"BioData" positions at Monash University in Australia
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management, distributed computing, and energy-aware computing, preparing them for impactful roles in industry and research. Key Components and Example Scenarios Predictive Resource Allocation and Load
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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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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
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The primary objective of this project is to enhance Large Language Models (LLMs) by incorporating software knowledge documentation. Our approach involves utilizing existing LLMs and refining them using data extracted from software repositories. This fine-tuning process aims to enable the models...
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My research focuses on the dramatic final stages of massive stars, exploring how they end their lives as gamma-ray bursts, supernovae, and kilonovae. To unravel these mysteries, I employ a combination of multi-wavelength observational data with sophisticated simulations. I am a member of various...
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I am an ARC Future (former DECRA) Fellow and lead the Structured Nanophotonics Group at Monash University. My research in nanophotonics explores the full potential and multi-dimensional nature of light, focusing on controlled light-matter interactions at the nanoscale. Driven by the fascinating...
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I supervise projects considering the evolution of accretion discs and their connection to observations. In particular, I consider discs that are warped or distorted (not flat). This geometry has been directly observed in planet forming discs around young stars (protoplanetary discs) and is...
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Many machine learning (ML) approaches have been applied to biomedical data but without substantial applications due to the poor interpretability of models. Although ML approaches have shown promising results in building prediction models, they are typically data-centric, lack context, and work...
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Seizure prediction algorithms will be developed using the one-of-a-kind ultra-long-term human intracranial EEG dataset obtained from the Neurovista Corporation clinical trial of their Seizure Advisory System, or data from other implantable or wearable devices. This involves consideration of both...
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We have several PhD opportunities available in areas such as Multimodal Large Language Models (MLLM) for human understanding, MLLM safety, and Generative AI. If you have published in top-tier conferences (e.g., CVPR, ICCV, ECCV, NeurIPS, etc.), you will have a strong chance of receiving a full...