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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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Contextual Data Analytics (ICDA) as a method to address contextual analysis challenges by bringing rich contextual information to the analyst’s workspace. Despite the technological capability to support ICDA
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feedback analytics! Project description: The ability to understand and act on feedback is one of the most powerful drivers of learning success. Despite decades of research affirming the value of feedback, it
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interested in data analytics, business strategy, or the digital creative industries, and provides practical experience in data collection, analysis, and applied industry research. Required knowledge R Packages
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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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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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nutritional data into a user-friendly platform, enabling consumers, restaurants, and policymakers to make informed food choices and reduce diet-related emissions. Required knowledge Data analytics and software
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) to support surgeons, operating room technicians, and other professionals in and around operating room activities. Particular areas that may be explored are: Immersive OR analytics: using XR to analyse data