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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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capture technologies. In this project, you will: Develop a 3D Digital Model: Create an advanced computational model of high-pressure mechanical seals. Apply Computational Fluid Dynamics (CFD): Simulate gas
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Identifying and validating models for complex structures featuring nonlinearity remains a problem at the cutting edge of structural dynamics, with applications ranging from civil structures
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PhD Studentship: Optimisation of Liquid Metal Filtration and Cleanliness in Nickel Based Superalloys
methods, and to develop tools for interpretation of model outputs. To apply models to discover filter structures / geometries for which the predicted filtration efficiency has been optimised. To undertake
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the organising principles of biological information processing, focusing on the underlying physics of computations and sensory environments. This exploration has led to developing models and advanced statistical
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need for materials that can endure extreme conditions while maintaining structural integrity. This Ph.D. project will explore the failure mechanisms in refractory metals and advanced ceramic coatings
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approach is to apply foundational techniques grounded in logic, semantics, and verification. This work takes place within the CYCLIC project: Cyclic Structures in Programs and Proofs, a collaboration among
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. ML-Based Predictive Models: Deep learning and surrogate modeling techniques will be employed to predict structural response under varying loads and detect early signs of fatigue or failure. 3. Real
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of engineering research activities. The Coastal Modeller will also be expected to contribute to the development of capabilities, processes, and standards to advance and maximize the impact of our work
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-assembly on a structural level, and correlate this with in vitro functional activity. At AstraZeneca, the student will be integrated into the Data Science and Modelling department within the Pharmaceutical