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of core scanning technology. Neutron tomography can provide 3D imaging, mineralogical and geochemical information with great promise for fast thorough characterization of ore deposits. As part of a
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leading medic-legal and engineering researchers on real-world crash data Join Australia’s only academic department embedded in a forensic medicine institute The Opportunity Are you a proactive early-career
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transformative sensing technologies. engineer novel fluorescent probes through advanced design, synthesis, purification, and characterisation techniques. perform high-resolution fluorescence microscopy experiments
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, accountable to the Head of the Experimental Mechanics group. The Person To excel in this role, you are required to have a PhD in Geoscience, Experimental Physics, or engineering, with demonstrated experience in
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Position Number: 0065657 Location: Parkville Role type: Full-time; Fixed-term for 4 years Faculty: Engineering and Information Technology School: Computing and Information Systems Salary: Academic
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for microbial analysis. You'll have the opportunity to work with cutting-edge mass spectrometry technology, develop semi-automated workflows, and collaborate with leading researchers across multiple Australian
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promoting bacteria, as well as a range of natural or engineered peptide elicitors, for the priming of plant defence pathways for enhanced viral tolerance. The successful candidate will develop and conduct
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this new technology useful in basic science, health & rehabilitation, and sport performance. The overarching goal is to design and test a smart garment embedded with these sensors, for advancement
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Apply now Job no:571702 Work type:Full-time Location:Geelong - Waurn Ponds Categories:Research Based at our Geelong, Waurn Ponds Campus Full-time and fixed term until March 2026 Level A $80,065 - $107,633 + 17% Superannuation (pro rata, part time) Why work with us? At Deakin you will have access...
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, Software Engineering, or a related field. Demonstrated experience in deep learning and large language model research, joint modality representation learning, knowledge graph construction, particularly in