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that has been generated in a prior laboratory-setting project. Specifically, we will integrate recent advances in artificial intelligence-based automated interpretation of medical images, and new knowledge
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you want to unravel the crystallization of phase change materials in heat storage devices? Do you like to work with advanced imaging techniques like CT and MRI? Do you want to understand the relation
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, including trans-differentiation of fibroblasts into neurons (iNeurons), development and screening of antisense oligonucleotides (AONs), live-cell imaging, and transcriptomic analyses. Laboratory work will
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lengthy processing times associated with sequencing. This PhD project aims to develop innovative artificial intelligence (AI) methodologies by integrating histopathology images and RNA sequencing data
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or biophysics, quantitative image analysis and programming experience with Python are beneficial but not required. We particularly encourage women and candidates from other groups which are currently under
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through a self-learning chip prototype, improving performance and durability in automotive applications. Specifically, this PhD project focuses on memristive materials as electronic realizations
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our research team in the field of mixed-signal IC design, focusing on the implementation of sense to compute paradigm. The ideal candidate will have a strong background in circuit design and experience
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? No Offer Description We are seeking a highly motivated PhD candidate to join our research team in the field of mixed-signal IC design, focusing on the implementation of physics-based computing paradigm
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for medical imaging, tailored for deep learning. The high-level goal of the project is simple: to use anatomical knowledge and existing knowledge as training data for deep neural networks (instead of manual
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atoms or molecules prior to the reaction. By combining this with resonance-enhanced multiphoton ionisation and velocity map imaging, we can probe the reaction products in high detail. This powerful