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fundamental and demand-driven research on modelling and analysis of complex social networks. This line of research is broadly focused on modelling, analysis and estimation of complex network models in
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. We are currently seeking a Research Fellow with experience in AI and machine learning research and development, with a focus on any or all of following application areas: Computer vision Generative AI
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/research/about-us/ AIML is the largest University based computer vision and machine learning research group in Australia, with over two hundred members including academics, engineers, research staff and
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flexible start/finish times, and genuine career progression opportunities via the academic promotions process. About You Completion or near completion of a PhD in Design, Interaction Design, Human Computer
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 2 months ago
tools and methods. Produce high-quality research outputs including computer code, digital products, workflows, design processes, and journal articles. Ensure that Indigenous perspectives are integrated
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experience in machine learning research and development, particularly with a specialisation in such areas as: digital forensics, computer vision, biometrics (face or voice recognition, etc.) and natural
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diverse audiences. Well-developed computer literacy, research skills, planning, organisation, and customer service abilities. About you as an Academic Level C Senior Research Fellow (in
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: Research Conduct high-quality research by collecting and processing weather radar data for Western Europe and estimate hail footprints at high spatial and temporal resolutions. Develop a comprehensive radar
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Biomolecular Engineering ) and Professor Gregor Verbic (School of Electrical and Computer Engineering ), in partnership with industry collaborators. Your key responsibilities will be to: develop, implement, and
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for – Selection Criteria: Essential: A PhD in remote sensing, geoinformatics, computer vision, or a related discipline. Demonstrated expertise in hyperspectral remote sensing, including pre-processing (e.g