45 data-visualization-analysis "https:" PhD positions at Monash University in Australia
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, computer vision, federated learning, foundation models, adaptation techniques, multimodal learning, longitudinal image analysis or related areas, evidenced through coursework, research projects
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AI infrastructure. The Opportunity This is an unprecedented opportunity for an outstanding data science and AI PhD candidate interested in brain data analysis and AI, supervised by Dr Mahsa Salehi
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of $37,145AUD per annum 2026 full-time rate (tax-free stipend), indexed plus allowances as per RTP stipend scholarship conditions at: https://www.monash.edu/graduate-research/future-students/scholarships
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successful. To be eligible, you must be an Australian or New Zealand citizen or Australian permanent resident. Please see other eligibility requirements and other details at the following link. https
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testing and assessment of device-assisted aerosol delivery under clinically relevant operating conditions. Data processing, image analysis, uncertainty assessment and experimental interpretation using
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own thinking, analysis and motivation. Applicants are responsible for verifying accuracy of all information, including references. Shortlisted applicants will be expected to discuss their statement
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: · Systematic review and meta-analysis · Evidence synthesis and critical appraisal · GRADE guideline development methodology · Living evidence methods · Clinical epidemiology
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social media and online platforms. The project will use natural language processing (NLP), large language models (LLMs), and network analysis to identify coordinated harassment, anti-gender equality
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of discourse, identity and meaning-making within online environments. Approaches such as semi-structured interviews, digital ethnography or social media data collection (including platform-based content analysis
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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