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applicants with a background or experience in: • Computational chemistry • Materials simulation • Scientific machine learning / AI • Molecular dynamics or DFT • Materials science or a related discipline
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with one of the following doctoral research projects. 1. AI-Aided Site Reconnaissance and Rapid Assessments for Settlement Upgrading How can spatial analytics, remote sensing, and machine learning models
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University entry requirements Transferring to Swinburne Recognition of prior learning in the workplace Study abroad in Melbourne Opportunities for Indigenous future students Guaranteed pathways from TAFE
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recognition Individual and group behaviour understanding Long-term behaviour prediction Multi-task learning and foundation models Zero-shot and open-set recognition Privacy-preserving AI using anonymised human
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the alumni office. Stay in the know Learn how to set up your UniMelb account to access perks and discounts. UniMelb account log in Access your account to update your personal details and access benefits
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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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practices in professional physics and students' engagement in these practices The role of agency in students learning physics practice A mixed-method, longitudinal study on factors related to retention in
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language processing, large language models, machine learning, network analysis, social media analytics, and large-scale analysis of online discourse and communities. This PhD scholarship will be based within
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" "Machine-learning-based imaging processing" webpage For further details or alternative opportunities, please contact: [email protected].
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to work with large volumes of data and produce accurate reports. The successful candidate will learn quickly, adapt to changing priorities, and take ownership of projects, while working effectively with