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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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imaging, flow cytometry etc. The chance to forge collaborations with experts in diverse fields at the Adelaide biomedical precinct. Ample professional, scientific and mentoring opportunities to develop
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materials systems at the molecular level with machine learning. The PhD Student will undertake a study analysing mass spectral imaging data streams in real time using machine learning workflows. A pathway for
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Qualifications Master or Honours About Swinburne University of Technology Swinburne’s strategy draws upon our understanding of future challenges. We choose to build Swinburne as the prototype of a new and
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Applied mathematics, fluid mechanics, high-performance computer simulations. Full time, fixed term position (3 years) at Hawthorn campus $34,700 per annum (2025 rate) About the Scholarship Higher
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Swinburne’s strategy draws upon our understanding of future challenges. We choose to build Swinburne as the prototype of a new and different university – one that is truly of Technology, of Innovation and of
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and hands-on experience with AI and computer vision. Solid programming skills in Python, especially with PyTorch. Practical experience with deep learning projects, including working with attention
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) and computer simulation (FEA) Experience in material characterisation and experimental testings Knowledge in impact dynamics Passionate and have interest in pursuing PhD degree. Experience in research
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. Your project will explore Stream Finishing, a cutting-edge surface engineering technology that offers unmatched precision and control over traditional methods. You’ll investigate how process parameters
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are molecules that exist in two forms, referred to as enantiomers, each being a mirrored image of the other. Different enantiomers share the same physical properties, but often have starkly different biological