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support the Australian Temperament Project (ATP) – a long-standing, multi-generational study of social and emotional development. This role will involve assisting with data collection and participant
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computer vision and machine learning research group in Australia -- and contribute to world-leading research projects at the CommBank Centre for Foundational AI This postdoctoral research position is part of
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 13 days ago
, and physical robot experiments would be an advantage. About the School and Host Area The School of Computing has a strong foundation in computing and information sciences at ANU. We are a transformative
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Strait Islander people and candidates from culturally and linguistically diverse backgrounds. For more information about staff equity at ANU, visit https://services.anu.edu.au/human-resources/respect
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analysing interview and interactional data. This will enable the co-design, testing, and implementing of a new training program to improve how assessments are communicated with clients and families, and to
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projects including complex data analysis (e.g., telemetry or genetic data) and paper writing The candidate will be working remotely (i.e. off-campus) providing excellent work flexibility Position Overview
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, experimentation, data analysis, student supervision, report writing and the communication of results to industry and through peer-reviewed journal articles. To Apply Applicants should submit cover letter detailing
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the direction of A/Prof Claudia Szabo in the School of Computer and Mathematical Sciences at the University of Adelaide. The project is a collaboration with Defence Science and Technology Group, within the Combat
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 15 hours ago
(The University of Western Australia), and will be actively involved in experimental design, data analysis, and dissemination of findings through publications and presentations. The successful candidate will have
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approaches to model uncertainty for learned computer vision systems, including dense prediction. The position will develop novel methods for deep learning in computer vision that accurately quantify their own