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Field
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assigned by Supervisor. Requirements PhD in Computer Science or related field Expertise in computer vision and vision-language models Experience with ML evaluation metrics and benchmarking Proficiency in
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University of New South Wales | Canberra, Australian Capital Territory | Australia | about 13 hours ago
. The position reports to Associate Professor Elizabeth Williams at UNSW School of Science and has no direct reports. Who You Are (skills and experience): A PhD in nuclear science, human-computer interaction
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ecology. Equipment Use of personal computer and proficiency in software and research statistical applications. Use of gas chromatography-mass spectrometry (GC-MS) and related research equipment. Working
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the following conditions: Scientific Area: Computer Science. Admission Requirements: Academic qualification: Master's degree in Computer Engineering, Computer Science, Electrical and Computer Engineering, or
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). Hands-on experience with game AI agents and/or GUI agents such as Mineflayer, Unity ML-Agents, or similar. Solid expertise in computer vision techniques, transformer architectures, and multi-modal
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working on innovative projects within the university. The research team is seeking a Research Fellow or Research Engineer with strong expertise in Human-Computer Interaction (HCI) and social science
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of computer and audio/visual equipment. We welcome and encourage applications from individuals of all backgrounds, especially those from groups traditionally underrepresented in the field of museum education
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learning or computer vision libraries; familiarity with Vision-Language Models (e.g., CLIP, BLIP) or scene-graph inference is a plus. Key Competencies Strong software development and debugging skills. Able
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engineering, information systems, geography, spatial planning, remote sensing and GIS, data science and advanced analytics, statistics and information management, as well as geographic information science and
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: Co-design of Context-aware Adaptive Mobile Authentication for Older Adults”, “2024.14974.PEX”, “DOI: https://doi.org/10.54499/2024.14974.PEX ”, funded by the Fundação para a Ciência e a Tecnologia, I.P