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/Statistics, Robotics, Physics, or related discipline, with an excellent academic record. Demonstrated expertise in computer vision and machine learning, including object detection, segmentation, and multi
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, or related discipline, with an excellent academic record. Demonstrated expertise and leadership in computer vision and machine learning research, including object detection, multi-object tracking, and
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Australian National University | Canberra, Australian Capital Territory | Australia | about 2 months ago
candidate will join Associate Professor Jean Wen’s research group, conducting independent, high-impact research at the intersection of AI/machine learning, computational biology, and RNA biology. The position
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focus of this Winanga-y Postdoctoral Fellowship role is to address a critical gap in agricultural technology adoption by investigating how AI and machine learning outputs can be better translated
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 23 days ago
expertise in one or more of a broad range of computational methods including but not limited to: machine learning / AI, spatial computing, computational creativity, text encoding, social media analysis
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engineering and a strong foundation in data science. You bring a passion for solving complex problems and a track record of research excellence in optoelectronic materials, machine learning, or related fields
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 2 months ago
: PD&PEWER Level A&B Postdoctoral - Research Fellow _ CSS.pdf This position will provide opportunities to: Conduct cutting edge research in machine learning, AI and algorithms, such as but not limited
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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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an advanced AI-augmented digital platform (AiCT-Med) powered by cutting edge machine learning models trained on multiple large, aged care datasets from providers across Australia. The platform is designed
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genetic variation into elite germplasm. This will require the integration and optimization of several technologies, including genomics, machine learning, genetic simulation, and speed breeding. This is a