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Field
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machine learning, computer vision, and medical image analysis, with publications in top-tier AI and medical image analysis conferences and journals, including CVPR, ICCV, ECCV, NeurIPS, MICCAI, TPAMI, TIP
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you You will have: PhD in developmental biology/biophysics/cell biology or in the final stages of PhD submission. Strong expertise in advanced confocal and/or light sheet imaging. Strong expertise in
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) learning numerical methods for wave-equation-based processing, imaging, and inversion. Wave phenomena are ubiquitous in science, and they extend to objectives ranging from global Earth discovery, to natural
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: PhD degree in Computer Science, Electrical Engineering, or a closely related field Strong research background in computer vision and deep learning Solid experience with multimodal learning, segmentation
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of today is constantly evolving to keep pace with advances in technology and globalisation, requiring individuals to adapt and develop new skills to ensure resilience through a culture of lifelong flexible
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/Qualifications We welcome applications from researchers who: Hold a PhD in neuroscience, biomedical sciences, physics, engineering, or a related field Have experience in brain imaging (e.g functional ultrasound
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and the highest in Australia. For further information on our school, go to - https://www.unsw.edu.au/engineering/our-schools/mechanical-and-manufacturing-engineering Skills & Experience PhD in
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learning/computer vision methodology. The focus of this project will be on the development of deep learning methodology for spatio-temporal medical image analysis, that is medical images that evolve over
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25th April 2026 Languages English English English The Department of Structural Engineering has a vacancy for a Postdoctoral Fellow in Microstructure-Informed Modelling of Fracture in Cast Aluminium
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for Science and Technology (FCT) I.P, under the following conditions: Scientific Area: Engineering Recipient category: Computer Engineering, Biomedical Engineering or related fields Identify the type(s) of