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with ultrastructural analysis. Manage, process, and analyze large imaging datasets generated from the project. Assist in mentoring and training PhD and undergraduate students in relevant techniques and
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Technological University, NTU, and National University of Singapore, NUS, and hosted by NTU. IDMxS is focused on development of core science to drive a paradigm shift in molecular detection and analysis to link
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We are seeking an ambitious and highly motivated postdoctoral researcher to help develop the next generation of fibre-based optical imaging and spectroscopy tools. This EPSRC-funded role is central
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, engineers, computer scientists, nuclear medicine physicians, …) towards the overall aim of enabling translational and physician-in-the-loop AI for medical imaging. Our research team is multicultural and
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translation of innovative miniature, hair-thin imaging devices we have previously developed (doi.org/10.1117/1.JBO.29.2.026002 ). These devices are designed to enable early and accurate detection of cancerous
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stochastic differential equations (SDEs); Extending recent quantum simulation techniques to accommodate non-physical processes found in generative diffusion modeling; Demonstrating a prototype of the quantum
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Processing. The project is part of the larger research project “AI4NaturalFood ”, in collaboration with the Department of Food Science, and the project is financed by the Novo Nordisk Foundation. Start date is
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). About you The post will require a motivated researcher with experience in image-based modelling of flow or biomechanics, from segmenting the images to performing CFD/FEM analysis. You will have a PhD and
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of endogenous DNA-processing machineries (Xenopus). We use a combination of biochemical and single-particle cryo-EM approaches. We are currently also developing in situ cryo-tomography imaging of replicating
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translation of innovative miniature, hair-thin imaging devices we have previously developed [https://doi.org/10.1117/1.JBO.29.2.026002]. These devices are designed to enable early and accurate detection