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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 2 months ago
. Position Overview The Robotics group at the ANU School of Computing is opening a 2-years Research Fellow (Level B) position to work on an exciting project in sequential decision-making under uncertainty
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The SQUASH Program is a prestigious Marie Skłodowska-Curie COFUND initiative offering 3-year postdoctoral positions in quantum science and technology. This 1st international call invites outstanding
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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
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application process here . ... (Video unable to load from YouTube. Accept cookie and refresh page to watch video, or click here to open video) About the position Are you ready to take your research career
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vision is to make clean energy accessible to drive climate action and enable children raised in off-grid and informal settlements to reach their full potential. We are looking for a Research Associate
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years. The nominal length of the PhD programme is three years. The fourth year is distributed as 25 % each year and will consist of teaching and other duties. The objective of the position is to complete
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. The postdoctoral researcher participates in a project set between classical public opinion research, (social) media (content) analytics and data linkage, and Computational Social Science. The goal is to capture
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Audition for Robots (ActivATOR)” under the direction of Dr Christine Evers. The position will be in the Vision, Learning and Control (VLC) Group, which is part of the School of Electronics and Computer
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of the ocean. About the position: The PhD research fellow will be part of the PhD programme in Computer Science: Software Engineering, Sensor Networks and Engineering Computing (https://ict.hvl.no). The research
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with strong background in Computer Vision and Machine Learning. Position Overview: In this position, you will investigate the existing solutions for assessing datasets and developing a novel tool relying