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of this programme. The profile PhD in computer vision, computational biology, physics or a related discipline Demonstrated expertise in image analysis and working with large-scale imaging datasets Strong expertise in
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-processing and analysis of cardiac imaging studies. Close collaboration with technical researchers within the cardiovascular imaging unit. Where to apply Website https://jobs.vhir.org/jobs/7511897-clinical
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the supervision of Dr. Merry Mani. The successful candidate will work on the development, validation, and translation of cutting-edge MRI techniques for imaging slow-flowing neurofluids and brain microstructure in
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of a 3D ultrasomics AI prognostic system for adolescent idiopathic scoliosis progression via longitudinal surveillance scans”. Qualifications Applicants should have experience in image processing and
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demonstrated experience in computer vision or analysis of pathology images. The appointees will participate in a multidisciplinary collaborative research project related to development of deep learning model
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an enthusiastic, proactive, and collaborative biologist to join Prof Witney’s Group in the School of Biomedical Engineering & Imaging Sciences, King’s College London. You will join a dynamic and successful
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image processing and/or data analysis. Proficiency in Python programming. Specific Requirements Full time and on-site within the LISTIC laboratory. Internal Application form(s) needed Offre emploi POST
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‘, bridges the different techniques developed within the cross-area imaging and gives support to all researchers dealing with image processing challenges. By focusing on automation and enabling correlative
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Max Planck Institute for Biological Intelligence (Martinsried site), Martinsried | Germany | 4 days ago
. Demonstrated interest in animal research, particularly rodent models (experience with mouse handling or physiology is an advantage). Experience with MRI data processing, image reconstruction, pipeline
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for the analysis of hyperspectral imaging data applied to pictorial layers, based on coupling physical radiative transfer models (two-flux and four-flux approaches) with machine learning methods. The researcher will