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with a new cutting-edge quantitative-trading company to push the frontiers of AI-aided decision-making in quantitative trading processes. As a PhD candidate you will: Design next-generation trading
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explore unconventional ideas, develop computer algorithms for data analysis, create new experimental approaches, and apply the technique in areas like biomedicine, materials science, and geology. My group
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, biology, engineering, machine learning / data science, coding. How to apply: This is an Expression of Interest process. To express your interest in applying, candidates must supply the following information
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biology: How do epigenetic features contribute to the regulation of the genome? We study how chromatin drives specificity for regulating gene expression. You will be dissecting the molecular features
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structural health monitoring, especially on computer vision, image processing, machine learning, deep learning, signal processing and data analysis techniques, are preferred. Application process To apply
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publications and research experiences in structural dynamics and structural health monitoring, especially on computer vision, image processing, machine learning, deep learning, signal processing and data
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the Monash Research Training Program (RTP) Stipend www.monash.edu/study/fees-scholarships/scholarships/find-a-scholarship/research-training-program-scholarship#scholarship-details Be inspired, every day Drive
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, the aim of this project is to develop and validate an experimental paradigm that can describe the dynamic processes underlying C2 agility and to characterise the situational factors by which C2 agility can
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the potential to change the world. There are prestigious Scholarships in 2026 for outstanding researchers from around the world to conduct paradigm-shifting research based at any of Western Australia’s five
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of outcomes by November 2024. Scholarship Details Maximum number awarded 1 Eligible courses All applicable HDR courses. Eligibility criteria Outstanding Computer Science or Engineering student Knowledge of data