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Multiple PhD Scholarships available - Cutting-edge research at the frontiers of Whole Cell Modelling
of the Bacterial Cell Envelope – From Molecular Structure to Metabolic Function: The cell envelope is the interface between a bacterial cell and its environment. MACSYS is currently modelling the structure and
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operation under reactive capture conditions. Unravelling reaction mechanisms and catalyst structure-performance relationships using advanced characterisation techniques and computational tools. Collaborating
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an ARC Linkage Project focused on developing an autonomous system for detecting and quantifying structural damage in infrastructures (e.g., bridges, grain silos) using computer vision, digital twins, and
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PhD Scholarship – Structural Aspects of Digestion Job No.: 679367 Location: Parkville campus Employment Type: Full-time Duration: 3.5-year fixed-term appointment Remuneration: The successful
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) investments could reshape the size, structure, and sustainability of Australian cities. The project brings together a world-class team of researchers from Monash University and international partners, including
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can provide powerful models for classifying and understanding protein structures, but expert supervision is required in the development, training and deployment of these models into automation scenarios
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Characterization Techniques Study the advanced electrochemical characterization methods. Gain deep insights into the reaction models associated with PCFCs. 3) Understanding of Electrocatalytic Performance and
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samples. -Applying Gross's (2015) process model of emotion regulation to the understanding of ADHD. -Exploring the definition/structure of ADHD statistically, and whether emotion regulation problems should
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, HNMR, BET etc.) will be employed to characterize the carbon nanofiber structures. For molecular level, understanding, DFT modeling will be employed. The project would require fundamental investigations
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advances in process-based crop models such as APSIM, their integration often remains limited. This project proposes to get more out of on-farm data streams and process models through their more formal