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models that support operational analytics, strategic reporting, automation, and emerging AI-driven insights. This role is critical to enabling data-informed decisions across academic, administrative, and
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professional and societal issues in technology-driven environments. The successful applicant must be willing and able to teach across a range of areas due to the interdisciplinary nature of contributing
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of modelling and decision-support frameworks relevant to engineering and infrastructure systems. You should possess a good honours degree and a PhD (or equivalent professional experience) in Mechanical
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and digital personalisation. Working collaboratively with marketing, sales and digital experience leads on the development and implementation of UNSW's data-and-technology-driven CX/DX innovation
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the production of spatially granular and engineering driven representations of model results. Experience working across disciplines in multi-institution and multi-stakeholder collaborations is desirable
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prompts for AI-driven tasks using modern frameworks to ensure effective agent performance and precise task execution. Collaborative Development - Work with other technical teams (e.g., Data Engineering
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on the track of Cyber-Human Physical Systems seeks researchers to advance Systems Science and Engineering by modeling human behavior in complex dynamic networks addressing global challenges. Emphasizing Cyber
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and Energy (HDS-LEE), the project offers an interdisciplinary research environment at the interface of bioengineering, computational biophysics, and data-driven modeling, with strong links to open
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. (phenomenological) models You are self-driven and able to work independently but also happy to contribute to a team effort in an enthusiastic group of scientists and engineers working on a common theme. You are
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includes, but is not limited to: photonic data processing and communication systems; AI-driven optical signal processing and network optimisation; machine learning for photonic systems modelling, control