522 software-engineering-model-driven-engineering-phd-position-"https:" positions at Monash University in Australia
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Engineering PhD - Indigenous Job No.: 693049 Faculty: Faculty of Engineering Location: Clayton campus Duration: 3.5-year fixed-term appointment Open to: People who identify as Aboriginal and/ or
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fully declarative, version-controlled infrastructure and software delivery. Developing and maintaining robust CI/CD pipelines using modern DevOps toolchains Engineering secure platforms, implementing
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PhD Scholarship - Zema Energy Studies Scholarship Domestic opportunities in Engineering, IT and Business and Economics Job No.: 692976 Location: Clayton / Caulfield Employment Type: Full-time
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domestic and international candidates for a fully funded PhD position in Civil Engineering focused on: Development of ultra-low carbon concrete systems Integration of biochar derived from organic waste
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I specialise in the numerical modelling of high-energy particle collisions , such as those occurring at the Large Hadron Collider. Accordingly, most projects I offer straddle the intersection
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the optical-to-radio wavelength range, from major surveys and space telescopes (e.g: Gaia, SDSS, JWST, Hubble, Roman, Rubin-LSST). These are analysed using advanced machine learning and data-driven methods. My
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passionate about building software that drives positive outcomes? As a Research Software Engineer at the Environmental Informatics Hub, you will play a central role in designing, building, and maintaining
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Doctor of Philosophy (PhD) or Master of Engineering Science (Research) Domestic Scholarship Opportunities at Faculty of Engineering Location: Clayton campus Employment Type: Full-time Graduate
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Doctor of Philosophy (PhD) or Master of Engineering Science (Research) International Scholarship Opportunities at Faculty of Engineering Job No.: 673887 Location: Clayton campus Employment Type
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The primary objective of this project is to enhance Large Language Models (LLMs) by incorporating software knowledge documentation. Our approach involves utilizing existing LLMs and refining them