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                Doctor of Philosophy (PhD) on Australian Green Ironmaking Scholarship Opportunities at Faculty of Engineering Job No: 685999 Location: Clayton campus Employment Type: Full-time Graduate Research 
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                Doctor of Philosophy (PhD) on Phase Transformations in Advanced Steel Design Scholarship Opportunities at Faculty of Engineering Job No: 685997 Location: Clayton campus Employment Type: Full-time 
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                This project aims to develop robust algorithms capable of identifying and analyzing fingertips extracted from both static images and video footage. Machine learning techniques, particularly computer 
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                MD-PhD Industry Leaders Scholarship (for returning MD-PhD students) Industry Leaders Scholarship This scholarship is awarded to Monash University medical students who have demonstrated a commitment 
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                The detection of human activities is crucial for effective monitoring purposes. The challenge lies in accurately and promptly identifying various types of activities from videos and images captured 
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                Computer Systems Engineering ● Materials Science and Engineering ● Mechanical and Aerospace Engineering For further information, please follow the link for each Graduate Research Degree ● 3291 - Doctor 
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                Doctor of Philosophy (PhD) or Master of Engineering Science (Research) Domestic Scholarship Opportunities at Faculty of Engineering Location: Clayton campus Employment Type: Full-time Graduate 
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                , S. Mohan and M. K. Ghantasala (eds.), International Conference on Intelligent Sensing and Information Processing (ICISIP), Chennai, India, 4-7 January 2004 (ISBN: 0-7803-8243-9, IEEE Catalogue Number 
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                Scholarship in CSIRO Industry PhD Program - Project 2: Techniques and Frameworks for Enabling Post-Quantum Cryptography (PQC) Migration Job No.: 678538 Location: Clayton campus Employment Type: Full 
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                also explore the role of AI to guide or suggest analytics. Patient Data Analysis, Procedure Planning & Organ Segmentation: we will explore immersive XR interaction techniques for patient data