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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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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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Full-time, continuing position within the Advanced Analytics, Planning and Enterprise Data team Lead the University's research analytics capability, driving research excellence, impact and
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across the University. You’ll play a key role in identifying opportunities to streamline, digitise and automate financial processes, while delivering insightful analytics through data extraction, reporting
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- $115,686 + 17% superannuation About the opportunity The Faculty of Engineering is currently seeking a Data Insights Analyst to extract and visualise data to derive insightful analytics, employing
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Adobe Experience Manager (AEM) and Adobe Journey Optimizer (AJO). Working across Digital Experience, Sales, Analytics, Marketing and IT, you will use customer insights, behavioural data and journey
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, including the analysis and interpretation of complex data, development of robust reporting and analytical solutions, and delivery of actionable insights to support operational, strategic and evidence-based
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2 x Full time, continuing roles in the Advanced Analytics, Planning & Enterprise Data team Be part of a diverse, agile, and fun team, advancing AI capability and produce high‑value analytics using
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influencing senior leaders, driving strategic outcomes and building analytical capability across teams. Advanced technical expertise in data analysis and modelling using tools such as Databricks, Excel, Power