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Field
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) as Art Historical Tool Network Analysis and Cultural Data Human–AI Collaboration in Art Historical Interpretation Digital Provenance Research and Collection Histories Computer Vision for Art Historical
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strong background in relevant areas. Key Responsibilities: To independently undertake research in computer vision and machine learning. To produce research reports and/or publications as required by
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intelligence, including machine learning and computer vision, robotics, and physics-based modelling, the DISC Lab pioneers new methods for monitoring, digitalization, and automation in construction. We
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generation of accessible and expressive digital musical instruments. You will design, develop, and evaluate novel music and human-computer interaction technologies that combine wearable motion capture
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-site datasets collected across international collaborators. The role will involve working closely with MRI physicists, clinicians, computer scientists, engineers and mathematicians to ensure high-quality
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is highly preferable Experience in material characterization, computational engineering, programming and computer aided design will be prioritized Work independently and in a structured manner, and
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utility-scale quantum computer in Brisbane. The QDA aims to pioneer the use of quantum computers for high-value decarbonisation projects such as improved battery chemistries, the development of new
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or individuals, Professional demeanor, high energy, dynamic personality and excellent communication and interpersonal skills, Proficiency with Microsoft Office and other computer applications, Proven verbal and
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for Academic Performance . About You You will demonstrate: Completion of a PhD in computer science, cyber security, human-computer interaction, or a closely related discipline with a focus on privacy, provenance
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University focused on advancing computer vision, multimodal AI, generative AI, and embodied AI. Founded in 2018, the lab has grown into a vibrant research group with around 40 members comprising faculty