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Research Fellow in Electromagnetic Field Mapping via Scanning Transmission Electron Microscopy Job No.: 682389 Location: Clayton campus Employment Type: Full-time Duration: 3-year fixed-term
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PhD Scholarship in Digital Mapping of Homemade & DIY Cultural Economies in First Nations Communities
PhD Scholarship in Digital Mapping of Homemade & DIY Cultural Economies in First Nations Communities Job No.: 681214 Location: Clayton campus Employment Type: Full-time Duration: 3.5-year fixed-term
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This project heavily focuses on maps (e.g. GoogleMaps or Open Street Map). We will explore various properties of road networks, including the granularity of road networks, routes and trajectories
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codebase, enhancing RESTful APIs, and applying best practice DevOps and Agile development methodologies. About you We’re looking for someone who brings: A degree in computer science, software engineering, or
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Recent advancements in foundation models have significantly improved AI systems' capabilities in autonomous tool usage and complex reasoning. However, their potential for location-based and map
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. A natural communicator and influencer, fluent in the language of executives, developers, and end users alike. Skilled at turning ambiguity into clarity – through journey mapping, business cases
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is highly complex. For the proposed PhD project, experimental data are already available that bring together maps of orientations of such crystals together with the deformation pattern generated during
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of our dynamic team. This team is the backbone of several core platforms, including Google Workspace, Okta, and Microsoft Identity Manager, and works closely with the Core Authentication Services team
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will have; Demonstrated experience with data migration in a large and complex environment with varying levels of data quality. Strong proficiency with migration tools, data mapping, profiling, cleansing
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significant associations and map cancer dependencies according to diverse molecular features. Deriving statistically significant features of “omics” data, integrating with functional dependency data to predict