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Australian National University | Canberra, Australian Capital Territory | Australia | about 2 months ago
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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, Software Engineering, or a related field. Demonstrated experience in deep learning and large language model research, joint modality representation learning, knowledge graph construction, particularly in
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institute that has developed an innovative collaboration research model, which seeks to create knowledge and influence thinking so that people can lead healthier lives. ISCRR conducts and facilitates research
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), clinical trials, disease surveillance, and the use of novel methods including Bayesian network, machine learning, social network analysis and dynamic data visualisation tools. Further information is
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and Host Area The School of Computing has a strong foundation in computing and information sciences at ANU. We are a transformative centre for research in artificial intelligence and machine learning
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Australian National University | Canberra, Australian Capital Territory | Australia | about 1 month ago
intelligence (AI), machine learning (ML) and vision, natural language understanding, and robotics, to build autonomous systems that can perceive, plan, and respond to their environment in pursuit of high-level
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requires strong technical skills in Python, R, machine learning models, cloud computing, edge computing, and FPGA. Additionally, you will contribute to the AI Centre by designing new AI subjects, supporting
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record of publications in top-tier venues such as SIGMOD, VLDB, ICML, NeurIPS, ICLR, or TPAMI. You may also: Have a strong background in machine learning, particularly foundation models for spatial data
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including the application of artificial intelligence and machine learning. You will engage with industry, government, and research collaborators, fostering partnerships that deliver outcomes aligned with
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software and advanced computer skills. Demonstrate the ability to learn new techniques quickly and deliver work in a timely manner. Have experience with advanced mass spectrometry platforms, particularly