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The proposed PhD project aims to build a machine learning/deep learning-based decision support system that provides recommendations on precision medicine for paediatric brain cancer patients based
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cutting-edge AI methodologies, focusing on combining data-driven approaches with physics-informed models to tackle challenges in MRI reconstruction. By integrating MRI acquisition physics directly into
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Balancing: Example: Imagine an e-commerce platform that experiences a surge in user activity during sales events. SmartScaleSys (S3) would predict this peak demand using ML models and allocate additional
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This PhD project is part of a larger project that aims to explain the uncertainty of Machine Learning (ML) predictions. To this effect, we must quantify uncertainty, devise algorithms that explain
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of cloud services (preferably AWS), containerisation (Docker/Kubernetes), and relational/non-relational databases (PostgreSQL, MongoDB) Experience designing, building, and deploying secure, reliable and
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maintenance of scientific equipment Assist with small animal model studies, data collection, and routine analysis in accordance with approved protocols and safety standards Manage laboratory operations
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, practices, relevant standards and legislation coupled with a sound understanding of operating system platforms and security models relevant to IT technologies and processes Advanced knowledge and experience
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research that addresses real-world challenges and you will demonstrate research leadership, including supervision of PhD students, and contribute actively to the Department’s educational, research, and
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model (with work from home) and flexible arrangements available Kick-start your career with Monash! The Opportunity You’ll be joining Monash at an exciting time in our history as we aspire to make leading
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financial management support for research projects and programs, including maintaining/using information systems, databases, websites and record-keeping systems. Providing high-level administrative support to