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international collaborations with clinicians, regulators, policymakers, and industry partners. You must have a strong background in machine learning, computer vision, and medical image analysis, with publications
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Profile: University degree (M.Sc., diploma or equivalent) in materials science, engineering sciences, or physics Experience in at least one of the methods of X-ray imaging, transmission electron microscopy
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– Imaging Technology Design Research Monash University Design Health Collab, nyein.aung1@monash.edu Applications Close: Thursday 31 July 2025, 11:55pm AEST Supporting a diverse workforce
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of chemical technology, applied physics and biomedical technology. Our fields of application include sustainable energy, process technology and materials science, nanotechnology and technical medicine. As part
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We are currently offering a PhD student position focused on developing new methods for molecular engineering that leverage live-cell imaging data and artificial intelligence (AI). The position is a
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, analytical, and kinetics modelling techniques. To realise the sustainable development of the blast furnace ironmaking process under increasingly stringent global carbon emission regulations, major
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the field, from tissue scaffold design in tissue engineering evaluation to surgery. The student will focus on establishing best practice for widespread applicability, building on past skin, heart, lung, brain
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for imaging plant tissues (rose cuttings) Realisation of a corresponding measuring stand and implementation of test series for imaging Realisation of a data processing routine for the automated detection
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orbital parameter extraction using image processing techniques. The ideal candidate should have a strong background in physics, engineering or a related field, as well as experience working with programming
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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