38 computer-science-image-processing-"Multiple"-"Humboldt-Stiftung-Foundation" PhD positions
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At the Faculty of Engineering and Science, Department of Materials and Production a position as PhD stipend in Muscle Neuromechanics and Ultrasound Imaging, within the doctoral programme Materials
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Biomedical Engineering conducts leading research in image analysis, computer vision, and machine learning, with a growing emphasis on generative AI and AI for scientific discovery. Our mission is to develop
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student, you will be embedded in the research groups Computational Imaging and Deep Learning (CIDL) and Applied Quantum Algorithms (aQa), part of the Leiden Institute of Advanced Computer Science (LIACS
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necessary or desired background A first class or an upper second class British Bachelors Honours degree (or equivalent) in an appropriate discipline. Subject Area Medical imaging, computer science & IT, AI
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. ✔ Close supervision by leading experts in bioelectroanalysis: 250+ publications (85% in Q1, 80% in D1 journals) 5 international patents Multiple technology-based startups ✔ Multidisciplinary research
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, performing data collection and processing of cryo-EM data. Setup of future hardware and software as the research technology is upgraded. Providing lab members support in data collection, image processing, map
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(bio-)chemistry, physics, and engineering expertise to study molecules and cells, taking advantage of optical and single-molecule imaging, molecular probes, molecular biology, and 'large' data analysis
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their evolution during catalytic operation and activation. You will apply advanced electron diffraction techniques (3DED, 4D-STEM tomography), atomic resolution STEM imaging (HAADF, ABF), EDX and EELS
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, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks Requirements: excellent university degree (master or comparable) in computer engineering or electrical
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diffusion models usually needs to access a pre-trained model multiple times sequentially to generate high-quality images or videos, which is time-consuming. The training process of diffusion models is also