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across HHMI. The Foundational Microscopy Image Analysis (MIA) project sits at the heart of AI@HHMI. Our ambition is big: to create one of the world’s most comprehensive, multimodal 3D/4D microscopy
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research support. Responsibilities Design and print 3D models, develop Python code, perform experimental spectroscopy tasks, analyze images through Python, write papers, and present research at conferences
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are seeking a Ph.D. student to join our multidisciplinary team developing a radical solution for better detection and treatment that uses ultra-thin snake-like robots and advanced optical imaging techniques
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School graduates over a thousand students who are ready to take on great ambitions and challenges. For more details, please view: https://www.ntu.edu.sg/eee We are seeking to hire a Research Fellow to
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digitally converted fundus camera, 3D printed ODocs universal smartphone fundoscopy adapter, 35mHz high resolution ocular ultrasound, HRT III corneal confocal microscopy, cloud-based ocular imaging archive
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/wireless/wireline systems, imagers, MEMS, medical/display circuits, power management, 2.5D/3D integrated circuits, and secure computing designs. Successful applicants will be expected to develop
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. Our research takes a multifaceted approach, combining imaging of organoids and animal embryos, mechanical measurements using atomic force microscopy (AFM) and other in-house technologies, as
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. This project will use state-of-the-art live-cell super resolution microscopy and automated image analysis to both visualise the 3D architecture of keratin networks in epithelial monolayers. You will explore how
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of imaging, both in acquisition speed and imaging depth, for applications ranging from biological systems to nanomaterials. This research is inherently interdisciplinary, combining expertise in optics
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Specialized areas: Deep Learning, Generative AI, Prompt Engineering, Conversational AI and Chatbots, Reinforcement Learning Applied domains: Machine Learning for Cybersecurity, AI for 3D Imaging, Recommender