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reinforcement machine learning models to enable efficient transpilation of quantum circuits on a wide range of quantum processor modalities and topologies. The key aim of the project is to minimise resource
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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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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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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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Collaborating Faculty/Team: Multidisciplinary team across the Faculty of Medicine, Nursing and Health Sciences, the Faculty of Information Technology, and Monash Malaysia Remuneration: Fully funded PhD
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PhD Scholarship in Multimodal Federated Learning and Medical Image Analysis Job No.: 695949 Location: Clayton campus Employment Type: Full-time Duration: 3-year and 3-month fixed-term appointment
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, segmentation, anomaly detection and learning in the context of non-stationary distributions. The candidate will also be connected to the Faculty of Information Technology. The Temporal Analytics Lab, directed by
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rate, pro-rata) About the Monash–Bayreuth Joint PhD Program The Doctor of Philosophy (Monash – Bayreuth) is an elite, international double-degree doctoral program delivered through a collaborative
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for an outstanding PhD candidate to undertake an Industry Linked PhD at Monash University in collaboration with Aervision Pty Ltd , an Australian AI company developing advanced video analytics solutions for critical
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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