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Doctor of Philosophy (PhD) in Machine Learning for In Situ Materials Characterisation Job No.: 698995 Location: Clayton campus Employment Type: Full-time Graduate Research Degree: 3291 - Doctor
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PhD Scholarship Develop AI and machine learning models to guide real-time, personalised treatment of paediatric brain cancer using multiomics and clinical data, within the internationally
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PhD Scholarship Opportunity - Processing intelligence for green metals using in situ X-ray characterisation and machine learning Job No.: 693787 Location: Clayton campus Employment Type: Full-time
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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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English language requirements . Not have previously completed a 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
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(density functional) theory, tight-binding and model Hamiltonians, quantum transport and machine learning, run on national supercomputers (NCI Gadi, Pawsey Setonix) and Monash's NVIDIA Blackwell AI system
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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, or human-computer interaction would be advantageous. How to apply We are seeking expressions of interest from qualified domestic candidates who wish to apply for this PhD opportunity. This position
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. The research combines robotics, computer vision, artificial intelligence, machine learning, control systems, and medical robotics to solve one of the most challenging problems in modern automation. Project