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PhD Scholarship Develop multimodal machine learning models to predict glioblastoma treatment outcomes using imaging and clinical data. Work with real-world data from John Hunter Hospital in a
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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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" "Machine-learning-based imaging processing" webpage For further details or alternative opportunities, please contact: haoran.ren@monash.edu.
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they bond in materials, but also develop transferable skills in scientific computing, data analysis and visualisation. "Machine learning for atomic-scale structure determination in thick nanostructures" (with
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factors involved in the onset and progression of dementia. Advanced computational methods, including bioinformatics pipelines and machine learning, will be employed to uncover putative biomarkers and
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, advanced soil analysis, and modelling. The research involves field work in Western Australia’s unique ecosystems, applying cutting-edge imaging, spectroscopy and molecular techniques, and leveraging machine
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accelerate the global shift to electric mobility. This PhD will build an AI-driven fleet-scheduling framework that learns from battery data in real time and optimises charging, operations and maintenance
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of system and data confidentiality and complete any other requirements. Desirable skills: Experience in programming (C, python, or similar). Knowledge in machine learning or distributed systems. How to apply
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. Understanding of or curiosity about machine learning, AI, or cloud computing tools used in agricultural analytics. Interest or experience in working with industry, government, or multidisciplinary research teams
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microfluidic fabrication and experiments 3D printing machine learning. Demonstrated programming skills (Matlab, C++, or Python). Desired Demonstrated ability to work independently and to formulate and tackle