36 machine-learning-modeling-"Linnaeus-University" PhD positions at Curtin University
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group has implemented state-of-the-art deep learning for underwater communications; deep learning models underwater environment based on real data. Our preliminary study shows that state-of-the-art deep
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university research into commercial outcomes. Under this program, PhD students will gain unique skills to focus on impact-driven research. This Project aims to develop a predictive machine learning model
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children. Mechanistic modelling of disease transmission involves the use of computer code to represent the epidemic dynamics of infectious disease spread within the community. This allows modellers
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record in medical research and innovation. The project will benefit from access to advanced computing facilities and specialized software for deep learning model development and CT scan analysis
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models for structural health monitoring of civil engineering structures. Digital twin models are used to interpret real time information from videos and images aided by computer vision techniques
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into the learning dynamics and learnt features of neural networks, this research has the potential to significantly improve the interpretability and reliability of AI models. Enhanced interpretability will enable
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tools to record and derive important contextual information. The student will also learn relevant statistical techniques such as Linear Mixed Modelling to compare between drills and competition
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submission within a couples therapy. Aims The project will aim to develop and test a model of how couples resolve imbalances along the dominance and submission dimension during couples therapy. Objectives
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publication Strong programming skills and familiarity with machine learning or finite element modelling Not currently receiving another scholarship of equal or higher value Application process Future student
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technologies, social structures, and networks. Effective C2 organisational systems are critical not only to military settings, but also to the operation of many civil domains, including emergency response