421 Computer-Science-"https:"-"Data-driven-Materials-Modeling"-"https:" positions at Monash University
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analysis, contextual analysis, audio feature extraction, and machine learning models to identify and assess potentially dangerous content. Similarly, computer vision models are implemented to analyse images
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the Healthy Working Lives Group within the School of Public Health and Preventative Medicine, this PhD is supported by an Australian Laureate Fellowship program, Reforming Work Disability Benefit Systems
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diverse data sources while addressing the challenges of limited computation, memory, and energy availability at the edge. Leveraging advances in multi-modal deep learning, sensor fusion strategies, and
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models (VLMs) on edge hardware. While VLMs have demonstrated strong capabilities in multimodal reasoning and understanding, their high computational and memory demands pose significant challenges for real
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spectroscopy and Gaia data of star clusters to decipher the mystery of the Lithium-rich giant stars" (with Prof John Lattanzio) "The origin of the heavy elements: Computer simulations of neutron-capture
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Casual Senior Research Officer - Interactive Machine Learning Web Development Job No.: 697404 Location: Clayton campus Employment Type: Casual Duration: 16-weeks Remuneration: HEW 7, $65.09 per hour (loaded casual rate) Amplify your impact at a world top 50 University through innovative...
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process natural language problem descriptions and translate them into executable code. This research seeks to streamline workflows across diverse domains, from software engineering to data engineering
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-disciplinary team of clinician scientists and computer scientists to develop diagnosis/predictive/treatment/robotics surgery models of diseases of interest using multimodal medical data, consisting of images
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develop team members, and deliver outstanding customer service. You will be a collaborative and proactive professional with sound computer skills, a commitment to safety and compliance, and the ability
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their performance both empirically and through controlled user studies. Required knowledge Strong background in computer science in general Familiarity and understanding of basic principles underlying automated