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to contribute to research on hybrid numerical-exponential asymptotic methods and their applications at the University of Sydney Base Salary, Academic level A $105,117 - $121,054 p.a + 17% superannuation About the
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dynamics in complex, large-scale project systems develop formal, computational, or simulation-based models to study how decisions, incentives, feedback, and learning evolve over time in megaproject
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impact. Your key responsibilities will be to: conduct high-quality, original research on AI-enabled decision-making dynamics in complex, large-scale project systems develop formal, computational
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, advanced characterisation and measuring methods for high performance perovskite devices relevant to commercial applications (terrestrial and space) Additional criteria include sustainability considerations
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in laboratory and analytical methods. What we’re looking for: A PhD or equivalent in a relevant field such as genetics, genomics, molecular biology, bioinformatics, fisheries science, or a related
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-method experimental programs and bring the independence, rigour and collaborative spirit needed to lead a major strand of a nationally significant research project. Selection Criteria: PhD in neuroscience
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to the development of new concepts, methods, and scalable systems for networked digital twins that support autonomous decision infrastructure for adaptive action with human oversight. This project is part of
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Postdoctoral Research Associate in Neuromorphic encoding for biological neurocomputation who has: a PhD (or near completion) in physics, engineering or a closely related field strong knowledge and skills in
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, enabled by agentic and embodied AI. Working under the supervision of Dr Neda Mohammadi , the successful candidate will contribute to the development of new concepts, methods, and scalable systems
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and AI/ML. In this role, you will advance innovative research that apply AI/ML to develop methods and tools to improve crop performance and resilience, contributing to solutions for global food security