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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 22 hours ago
closely with the Facility’s Head, Business and Operations Manager and lead Facility team members. They will also interact with industry and external users of the ANU Facility, providing high level advice
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interact with industry and external users of the ANU Facility, providing high level advice to prospective clients, overseeing interactions between clients and team members, contributing to the training
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and data-poor settings. Key research areas include stress prediction, reservoir deformation, fault reactivation, and the interaction between injected fluids, and rock properties. This project offers
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position is funded through an ARC Discovery Project entitled “Unravelling the role of amyloids in viruses (DP250101215)”, and will focus on the discovery, characterisation and biological interactions
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for the Institute is to optimise human interaction, and wellbeing across lifespan. We strive to solve the problems that matter most through the themes: sensing and perceiving, interacting with each other, and
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Excellent organisational and time management skills relevant to supporting the ongoing management of a research project and team. Excellent interpersonal and communications skills appropriate for interacting
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record of computer programming. Experience in numerical relativity and/or numerical simulation of quantum field-detector interaction Strong written and oral communication skills. Demonstrated ability
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into the broader ACCESS Earth System Model 3 (ACCESS-ESM3), in close collaboration with the ACCESS-NRI team. The project will answer fundamental scientific questions about the interactions between ice sheets
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until June 2027 • Location: Macquarie University (Wallumattagal Campus, North Ryde) Join a leading ecology and evolutionary biology research team to uncover the role of ecological interaction networks as
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closely with an industry partner, you will generate cutting-edge insights into protein structures and protein-ligand interactions using in silico approaches such as bioinformatics, modelling and docking