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complex public health issue underpinned by a range of environmental, commercial, social, and cultural factors. Alcohol use amongst young people has declined over the past three decades, however there has
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the diverse range of knowledge and skills of CaLD customers and employees. This project aims to use social identity theory and role theory to develop a comprehensive conceptual model for the process by which
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results accurately and draw meaningful conclusions to inform further research and process improvements. Background in modelling and simulation using simulation software. Background in Techno-economic
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, teams are adapting to significant technological advances accompanied by great volumes of incoming data. Such changes have the potential to improve capabilities in complex and uncertain conditions, but
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, applied maths, physics, chemistry, computer science, computational modelling, earth science or similar. Strong programming skills. Experience in making gas flux measurements Excellent project management
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We invite applications for a PhD studentship at RMIT university funded by Enzide Technologies. The project aims to develop novel dry particulate protein/enzyme complexes. The project aims to enhance
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PhD Scholarship in ‘Using nanoparticles to enhance the immune response and improve vaccine efficacy’
of disease and are readily available for many diseases, however there is a need for vaccines to complex diseases such as malaria and cancer. Vaccines to complex diseases are more difficult to design and
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The PhD candidate will gain intensive knowledge in innovative processing protocols for complex mineral processing, column leaching, and mining site environmental science through hands-on experiments
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challenge is to combine our best theories of fundamental physics to model what happens at ultra-short distances. This project will generate new knowledge at this interface by using a novel approach inspired
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machine learning approaches show issues in model performance and efficiency and vulnerability towards the application of noise over a large number of distributed models. These issues should be overcome by