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Field
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and field experiments to develop and test potential solutions for imperfect products, and agent-based modeling to examine the effects of the solutions across the population and over time. You will
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, integrating AM into supply chains demands new models and methods. In this PhD project, you will: develop dynamic supply chain design models that enable the repositioning of AM equipment based on Defence
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on addressing the complexity of the device-software-application-data design space, enabling systematic and efficient exploration using modeling and simulation tools.## Key Responsibilities- Identify and
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light orientation—to form and maintain swarms. To complement the fieldwork, you will conduct lab experiments on a model species (e.g. Culex pipiens) to test specific hypotheses about sensory-driven flight
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lithium-ion battery (BLIB) with fast charge/discharge (1 min) and high energy density. Working with three PhD candidates and one postdoc, you will help synthesise a conductive anode within a bicontinuous
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the development of a Virtual Training Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and
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strategies for SNAREopathies". We use technology to produce human neurons and create human neuronal networks in vitro that severe mental disorders, such as the model SNAREopathies are a diverse group of brain
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models based on survey and secondary data. Creative approaches to combining and leveraging various data sources are highly encouraged! The selected Ph.D. candidate will benefit from our outstanding
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. As part of this PhD, the candidate will: - Conduct an integrative review of established competency models - Create assessment tools (which may include use of AI tools) to measure CLMA proficiency
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explore how to combine data-driven and model-based approaches to assess the quality of returned parts, monitor in-process performance in real time, and support intelligent decisions on remanufacturing