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can derive by hand and build up to large-scale calculations. You will need a background in condensed matter physics / quantum mechanics and an interest in coding (Python); no prior experience with
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PhD. Be able to commence the Program in the year of the offer. The ideal PhD candidate will have: A strong background in machine learning, deep learning, and software programming Proficiency in Python
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of the offer. The ideal PhD candidate will have: A strong background in machine learning, deep learning, and software programming Proficiency in Python and machine learning frameworks such as PyTorch
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have: A strong background in software security, linear algebra and software engineering Proficiency in Python and machine learning frameworks such as PyTorch (required) Knowledge of quantum computing
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learning, and software programming Proficiency in Python and machine learning frameworks such as PyTorch (required) Knowledge of quantum computing or quantum algorithms (advantageous but not essential
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learning, materials characterisation or computational materials science. Previous experience with machine learning, computer vision, graph neural networks, Python, SEM/EBSD, XRD, image analysis
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Python and/or Julia using LINUX-based OS. Communication of findings through journal publications, conference presentations and project reports. Candidate Requirements Applicants must satisfy the criteria
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or publications; Have experience with Python programming and the use of high-performance computing infrastructure for AI research; Have excellent written and verbal communication skills; Have the ability to work
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experience, deemed equivalent by the GRC (or delegate). The ideal PhD candidate will have: A strong background in machine learning, deep learning, and signal processing Proficiency in Python and machine
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should ideally have experience in: Essential Deep learning and machine learning Computer vision Python programming PyTorch or TensorFlow Strong mathematical and analytical skills Desirable Video