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interacting with these systems, including difficulties understanding eligibility requirements, producing relevant documents, and navigating complex administrative processes. The PhD project will generate in
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-dependent process to a device-assisted platform by integrating zero-net-mass-flux synthetic jets, piezoelectric actuation and quantitative aerosol diagnostics into an adaptive soft-mist inhaler. Funded
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new x-ray imaging techniques from the synchrotron to the laboratory Transforming breast cancer imaging with x-ray phase contrast Webpage: https://xrayimagingmonash.wordpress.com/ For further details
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experience, deemed equivalent by the GRC (or delegate). The ideal PhD candidate will have: A strong background in machine learning, deep learning, and signal processing Proficiency in Python and machine
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should ideally have experience in: Essential Deep learning and machine learning Computer vision Python programming PyTorch or TensorFlow Strong mathematical and analytical skills Desirable Video
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workshops. Selection criteria: Prospective applicants must satisfy Monash University’s PhD entry requirements as outlined in the Monash Graduate Research Admission Procedure , including: Valid and current
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requirements, including English-language proficiency skills, to undertake a PhD in the Faculty of Arts are available at arts.monash.edu/graduate-research/application-process/ . Applicants should ensure
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research themes including metallurgy, biomaterials, polymer chemistry and processing, and advanced materials. The Opportunity Applications are sought from outstanding candidates for PhD study in
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the Integrated PhD program application process outlined on the Monash Business School website. Briefly, the process is: Assess your eligibility using the interactive tool on the webpage under Step 1 (i.e. the PhD
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involving patients and communities more deeply in the process. An important part of this project (WP-1) will be to understand the impact of patient data on funding decisions for medical technologies. We will