355 web-development-"https:" "https:" "https:" "Newcastle University" positions at Monash University
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the power of LLMs to develop advanced computational methods for the detection and mitigation of misinformation and disinformation. More specific objectives are: To investigate the effectiveness of large
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resources to avoid downtime, adjusting dynamically as traffic fluctuates. For researchers and students, this component focuses on developing ML models to predict resource needs, improving load distribution
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these challenges, calling for the development of responsible AI systems that are transparent, trustworthy, and aligned with human values in educational contexts. This PhD project aims to design, develop, and
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period to a 'developing' country. Total scholarship value $6000 Number offered Two See details Bachelor of Education (Honours) in Secondary Education and Bachelor of Arts Rebecca Having a scholarship has
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. Working under the guidance of the Professor of the area, the role helps coordinate codesign activities, develop bespoke materials and surveys, and assist with data collection, analysis, and research
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The United Nations Development Programme has identified access to information as an essential element to support poverty eradication. People living in poverty are often unable to access information
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, yielding negligible performance gains or even inducing catastrophic forgetting. To bridge the gap between theoretical AL and real-world deployment, this PhD project will develop resilient active learning
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a unique opportunity to influence and develop the Faculty’s curriculum and research training programs, thereby shaping the future of educational research and practice. This position demands a special
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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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these issues is critical for building trustworthy multimodal AI systems. Research Objectives The goal of this PhD project is to develop scalable Bayesian uncertainty estimation frameworks for single- and multi