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, machine learning, and image processing techniques Strong candidates with electrical, mechanical, and biomedical engineering backgrounds can also apply. To be eligible for this scholarship, you must: Meet
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and reform options and investigate potential mechanisms, processes and organisations through which systematic change can ideally be influenced and achieved. As a means to address unsustainable resource
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The aim of this project is to describe ion conduction and activation/inactivation processes by employing molecular dynamics and statistical mechanical methods. The expected outcome is an improved
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) to conduct research in organic resource recovery project. The project will provide numerous development opportunities including: Developing lab-scale and pilot scale experimental rigs Developing numerical
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skills Experience with nanoparticles for drug delivery or diagnostic applications Familiarity with biological systems and cellular targeting mechanisms Knowledge of computational tools for modelling
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for: Passionate about optimisation, experimentation, AI and machine learning, and application of these technologies to business problems; Good coder with at least one of the major programming languages. Python is
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instrumentation and experimental trials is desirable. • Ability to establish rapport with multidisciplinary industry representatives, for example related to Controlled Environment Agriculture, is desirable. How
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of analytical techniques of rock characterisation • Prior experience in experimental geochemistry (water-rock reactions) is preferred • Some knowledge of geochemical modelling is encouraged but not mandatory
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polymer science. Problem solving skills/experience in applied chemistry, mechanical or electrical engineering. For further information, please contact A/Prof. Ken Chiang (E: Ken.Chiang@rmit.edu.au
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-field imaging. In the X-ray imaging group at Monash, we develop these novel methods, working across theoretical foundations, experimental realisation, and practical applications. My research focuses on X