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Overview This project proposes a novel quantum-enhanced learning analytics framework for higher education, focusing on early identification of at-risk students and optimisation of intervention
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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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them The Opportunity Join the Finance portfolio as a Business Analysis and Improvement Officer and lead complex analytics, process improvement and change initiatives that support operational excellence
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graphs or multi-agent reinforcement learning. Strong programming skills in Python and AI frameworks such as PyTorch, JAX or TensorFlow, combined with excellent analytical, problem-solving, communication
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The Professional Experience Lead Coordinator will play a key role in delivering employability, Work-Integrated Learning (WIL) and placement initiatives. Working closely with the Associate Dean, Professional Pathways
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related field. Strong analytical and manuscript preparation skills, experience analysing complex clinical or biological datasets and the ability to develop well-documented code in R, Python or another
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materials discovery with cutting-edge high-throughput platforms, robotics, machine learning, and autonomous experimental workflows. Access World-Class Facilities: Based in the Department of Chemical and
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seamless and efficient data loads and post migration validation processes. The ideal candidate has strong analytical skills, a keen eye for detail, and the required technical skills to develop data
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of observational data, comparison of multi-wavelength data against model predictions, and/or demonstrated knowledge of multi-messenger science. The successful candidate will also have demonstrated analytical and
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natural language processing, multi-agent systems, reinforcement learning, or knowledge representation would be advantageous but is not strictly required. Strong analytical and problem-solving abilities, as