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This project aims to develop robust algorithms capable of identifying and analyzing fingertips extracted from both static images and video footage. Machine learning techniques, particularly computer
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as assigned by the project lead Key Selection Criteria A bachelor’s or master’s degree in information technology, computer science, software engineering, or a related field. Strong proficiency in web
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biology with a major focus on live cell imaging. An emerging profile in super-resolution microscopy, and confocal microscopy of mitochondria dynamics in temporal resolution. Demonstrate capabilities in
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or engineering Strong computer science skills and some experience with statistical, machine learning, and image processing techniques Strong candidates with electrical, mechanical, and biomedical engineering
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You Completion or near completion of a PhD in the computer science or relevant field. Demonstrated experience with multi-modal imaging (RGB, thermal, spectral) and 3D data acquisition (e.g., LiDAR
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innovative computer-vision solutions to advance new cotton varieties. By incorporating expertise in plant phenotyping, engineering, image collection, computer vision, and deep learning, you will essentially
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internal grant funding for research. Maintain safe operation within group laboratories, following relevant OH&S requirements. Develop a coherent research program and an emerging research profile. Support
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sciences at ANU. We are a transformative centre for research in artificial intelligence, computer vision and machine learning, computer systems and software, and theoretical foundations of computing. We span
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to join a multidisciplinary team as a Research Fellow in Systems and Computational Neuroscience. This exciting opportunity is perfect for someone passionate about applying advanced imaging and computational
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and operation of ultrasound imaging systems, ultrasound image recognition and comprehension, patient assessment, care and communication, critical thinking skills, ultrasound physics, occupational health