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completion); Applied for admission to a PhD program at an Australian university or be a student enrolled in their first 12 months of study in a PhD program at an Australian University; A university supervisor
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Image processing and computer vision Experimental data analysis and uncertainty quantification Piezoelectric actuation, acoustic systems or electronic driver development Eligibility and Project
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electrowinning ● Unlocking critical energy materials from mining and industrial wastes Through the CREST PhD Program, you will: ● Undertake research that addresses nationally significant challenges in critical
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processes and systems KSC 8: Advanced computer literacy and proficiency in Microsoft Excel and spreadsheet-based data analysis. This criteria is essential. Diversity is one of our greatest strengths at Monash
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-disciplinary team of clinician scientists and computer scientists to develop diagnosis/predictive/treatment/robotics surgery models of diseases of interest using multimodal medical data, consisting of images
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. The Opportunity This interdisciplinary PhD project between IT and the social sciences will explore the development of computational approaches for detecting and analysing misogynistic backlash ecosystems across
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submit your resume and a short statement addressing why you would make a great Lecturer/Demonstrator in our program. Recent Professional practice is required for this role. Please detail your recent
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. Required knowledge Strong background in machine/deep learning, computer vision, or applied statistics. Solid programming skills in Python and experience with deep learning frameworks (e.g., PyTorch
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ERP - Senior Business Analyst - HR stream Job No.: 697785 Location: Mulgrave Employment Type: Full-time Duration: Fixed-term appointment until August 2027 Remuneration: $145,062 to $153,976 pa HEW Level 09 (plus 17% employer superannuation) Amplify your impact at a world top 50 University Join...
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Recent advances in artificial intelligence have produced highly accurate diagnostic models across a wide range of medical applications. However, these systems often provide little insight into how decisions are made, limiting clinician confidence and adoption in healthcare settings. Large...