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computing applications—mainly for a SWaP-constrained AV—using hybrid electro-photonic accelerators. We propose to design and prototype a complete electro-photonic computing (EPiC) system (CPUs + accelerators
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provides a diverse, inclusive and supportive environment. Alumni from the lab have won prestigious awards and received multiple job offers from top research institutes and medical imaging companies in the US
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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Join Our Team at the School of Biological Sciences, Nanyang Technological University, Singapore The School of Biological Sciences (SBS), part of the College of Science, was established in 2002 with a mission to advance biological and biomedical sciences. At SBS, our research spans various...
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research and development. Here, you can apply your engineering talent to develop new life-saving technologies – for example, medical imaging, wearable devices, surgical robotics and laboratory-grown tissues
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and/or attending a non-degree course taught by a higher education institution in collaboration with an R&D unit. Experience in image and audio capture (video and photography), video editing (Adobe
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Support”, through analysis of MR Diffusion Weighted Imaging and MR Spectroscopy and leading other members of the wider team Specific aims of the project To prospectively evaluate non-invasive pre-surgical
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(EBI), by the Norms for Grant Assignment and Management within R&D Projects, by the Code of Administrative Procedure (CPA), all in their current wording, and by other applicable national and community
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems