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of system and data confidentiality and complete any other requirements. Desirable skills: Experience in programming (C, python, or similar). Knowledge in machine learning or distributed systems. How to apply
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microfluidic fabrication and experiments 3D printing machine learning. Demonstrated programming skills (Matlab, C++, or Python). Desired Demonstrated ability to work independently and to formulate and tackle
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expertise in research methodology or willingness to learn. Well-developed computer skills. Application process Expressions of interest are invited to be submitted electronically to Professor Judith Finn via
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supervisor: Dr Kane Middleton Other supervisors: Dr Danielle Vickery-Howe (LTU), Dr Joseph Stone (SHU), Professor Jon Wheat (SHU) This PhD explores how people learn to move safely and maintain stability
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challenging for clinicians and pregnant women. Digital health records, advances in big data, machine learning and artificial intelligence methodologies, and novel data visualisation capabilities have opened up
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science technologies, and this is a perfect training opportunity for those who is interested in machine learning, data mining, artificial intelligence, and bioinformatics. High-performance computing may
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at Swinburne Early Entry Program University entry requirements Transferring to Swinburne Recognition of prior learning in the workplace Study abroad in Melbourne Opportunities for Indigenous future students