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slide imaging analysis in computational pathology is essential. Applicants should have a solid publication record and demonstrated experience in computer vision or analysis of pathology images
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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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multimodality deep learning model development in different sarcomas. Publications in related fields will be a strong advantage. Opportunities for publication and independent development will be available
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research skills in different contexts, working with mentors with different disciplinary and substantive expertise in the social sciences. The successful candidate will have the chance to work with leading
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, transcriptomics data, Nanopore long read sequencing analysis and/or multimodality deep learning model development in different sarcomas. Publications in related fields will be a strong advantage. Opportunities for
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research team to conduct data analysis for different types of data, including genomic/metagenomic sequencing data, ecological surveillance data, as well as development of analysis pipeline. Working off
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multimodality deep learning model development in different sarcomas. Publications in related fields will be a strong advantage. Opportunities for publication and independent development will be available
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, transcriptomics data, Nanopore long read sequencing analysis and/or multimodality deep learning model development in different sarcomas. Publications in related fields will be a strong advantage. Opportunities for
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include coordinating the peer‑review process; communicating with authors and referees; assisting with special issues and symposia; maintaining the journal’s editorial workflow; and contributing
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advancing the use of computer vision, deep learning, and machine learning for analyzing medical imaging modalities such as CT, MRI, X-ray, and ultrasound. Research areas include image segmentation, detection