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This PhD project focuses on the design and evaluation of hybrid quantum–classical algorithms for large-scale data analytics and optimisation problems. The research will investigate how quantum
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of analytical data to guide the generation of highly accurate 3D/2D molecular graphs or SMILES representations. Research Aims and Objectives This project aims to develop a robust, data-efficient deep learning
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Director, Marketing Technology, Data & Analytics Job No.: 689487 Location: 211 Wellington Road, Mulgrave Employment Type: Full-time Duration: 3 year fixed-term appointment Remuneration: A
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/Prof Linda Corrin, Asst Prof Yizhou Fan, Adj/Prof Rafael Ferreira Leite de Mello, and A/Prof Lan Yang. They will be based at the Centre of Learning Analytics at Monash. The PhD 1 project will focus
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to real-life data. The goal is to generate new knowledge in the field of time series anomaly detection [1,2] through the invention of methods that effectively learn to generalise patterns of normal from
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. If successful, you will join Dr. Roberto-Martinez Maldonado, Prof. Dragan Gasevic, and a strong team of academics, researchers and other students at the Centre of Learning Analytics at Monash University
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PhD Scholarship - Novel methods to enhance the use of routinely collected linked data for the evaluation of government policies related to healthy ageing Job No.: 691415 Location: Frankston
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to these protein structural characterisation scenarios. We will explore the applicability of advanced immersive visualisation and visual analytics using Augmented and Virtual Reality environments in visualising and
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information that is encoded in the x-ray wavefield as it passes through the sample. My research aims to tap into the wavefield phase to reveal weakly-attenuating objects like the lungs that are almost invisible
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electromagnetic signatures, primarily focussed on linking the data from these exciting experiments with our theoretical understanding of gravity and the most extreme regions of the Universe. I am a member of the