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of potential options for implementation. This will include prototyping and testing of various implementation options, analysis and documentation of results. Project 2 - Future Power System Modelling: As part of
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Technology (SET) This position plays a vital role in developing advanced theoretical tools and models for superconducting quantum materials research, contributing to leading-edge defence-related technologies
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The Adelaide Graduate Research School (AGRS) and the Adelaide Park Lands Association are partnering to create an internship opportunity for a University of Adelaide PhD students, to contribute to a project that will raise public awareness of this essential green space. The Adelaide Park Lands...
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Modelling to join an interdisciplinary team investigating how ecological traits, environmental changes, and anthropogenic pressures have shaped historical declines and extinctions of Australian mammals
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Martin Australia invite applications for a project under this program, exploring the development of Physics Informed Neural Networks (PINNs) for efficient signal modelling in areas such as weather
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for deployment across the network Provide high-level statistical support to APPN projects, including preparing experimental designs, statistical modelling of plant phenotyping data, and preparing figures and
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), mouse models, fluorescence microscopy (confocal), genomics, epigenetics, cell biology and biochemistry techniques (e.g., RNA/ChIP-seq, mass spectrometry). Successful track record in conducting and driving
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individual to work on an exciting modelling and simulation project, involving extensively applied work at the intersection of software engineering research and modelling and simulation, with real-world testing
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). Proficiency in numerical modelling, data analysis and instrument control in languages such as Matlab, Python, C/C++, etc. Familiarity with sensor technologies and applications, machine learning, and electronics
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group to work on a project developing provable network security methods that use higher-order graph-based abstractions to model networks and network security problems. Scalable algorithms developed