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protocols for diverse model organisms, with general supervision. Perform hands-on bench research, including tissue preparation, sample processing, and microscopy imaging to generate high-quality datasets
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Role We are seeking a highly motivated and experienced computer scientist to lead the analysis and interpretation of multimodal imaging, including spatial transcriptomics, single cell and large-scale
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, and building worldwide collaborations aimed at tackling the challenges posed by terabyte and petabyte-scale imaging data processing, visualization, and dissemination. Members of the ABC have access
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Are you pioneering molecular tools and applying advanced imaging strategies to uncover how microbial communities are organized and interact in space and time? If so, we invite you to join The
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Automated Generation of Digital Twins of Fractured Tibial Plateaus for Personalized Surgical plannin
respecting the specific constraints of emergency situations. Required Skills and Candidate Profile The project is intended for a candidate with: ➢ Skills in medical image processing and deep learning adapted
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at tackling the challenges posed by terabyte and petabyte-scale imaging data processing, visualization, and dissemination. Members of the ABC have access to leading - edge imaging and computing hardware, as
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position is on a 9-month service period with an anticipated start date of September 16, 2025. We seek to hire a faculty member in medical imaging physics. The successful applicant will be expected to conduct
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and testing angiogenic peptides. The role involves both in vitro (cell culture, imaging, molecular biology) and in vivo methodologies. Reporting to the principal investigator, the associate will also
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high-throughput screening using genetic and imaging tools. Apply molecular and cellular assays to study inflammatory processes. Analyse integrative omics datasets using bioinformatics and machine
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(or comparable deep learning models) for image analysis. Demonstrated expertise in digital pathology concepts, including image processing, feature extraction from whole slide images, and working with large-scale