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biochemistry techniques, confocal laser scanning microscopy, and live cell imaging with automated fluorescence microscopes to address and answer the research questions. The research team is located in the Sir
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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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2) and ensures a smooth transition to partners for later stages of development. By connecting science, innovation, clinical trials, regulatory processes, and product development, NIVI aims
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, such as molecular data (e.g. omics), imaging, electronic health care records, longitudinal patient and population registries and biobanks. To be a doctoral student means to devote oneself to a research
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experience with X-ray methods and imaging Have preferably some additional experience in the biomedical domain and/or in image processing Have preferably some experience using ML models and tools (e.g
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degree in biomedical sciences or related life science discipline We are looking for candidates with hands-on experience or a strong interest in spectral imaging techniques, confocal microscopy, and
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of electron microscopy imaging and spectroscopy to reveal the structure–property relationships that govern molecular adsorption mechanisms. This interdisciplinary project is fully funded by DTU’s PhD grant
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friction models. Integrating Experimental Data: Collaborate with experimental teams to incorporate data from calcium imaging, confocal microscopy, and high-resolution video recordings. Use experimental data
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and hands-on experience with AI and computer vision. Solid programming skills in Python, especially with PyTorch. Practical experience with deep learning projects, including working with attention
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for candidates with hands-on experience or a strong interest in spectral imaging techniques, confocal microscopy, and bioinformatic analyses Experience in mouse work is highly desirable Interest in