10 postdoctoral-image-processing-in-computer-science Postdoctoral positions at Stanford University
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Application Materials: Research environment The Postdoctoral Scholar will join an interdisciplinary research program spanning high-temperature reacting flows, aerosol science, carbon nanotube synthesis
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(but not limited to) the qualifications of the selected candidate, budget availability, and internal equity. Pay Range: $80,000 - $85,000 Postdoctoral Research Fellow - Computational Neuroscience and
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biology and offer training in human histology, statistics, omics data analysis, computer vision, grant writing, and scientific publishing. Required Qualifications: 1. A doctoral degree (PhD, MD
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Stanford University required minimum for all postdoctoral scholars appointed through the Office of Postdoctoral Affairs. The FY27 minimum is $79, 056. Postdoctoral Scholar – Bacterial Chemistry, Microbiology
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computational biology, cancer biology, and/or molecular biology preferred • Experience in image processing and analysis also preferred • The candidate will report directly to the Principal Investigator and will
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motivated and skilled postdoctoral researcher to lead projects related to PhacoTrainer—computer vision models for cataract surgical video recognition. Project themes will include validating PhacoTrainer
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, AI/ML, biomedical image analysis, multimodal integration, quantitative pathology, statistics, or computational modeling. Cancer Biology: Tumor microenvironment, cancer immunology, stromal/ECM biology
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Medicine are seeking to appoint a Postdoctoral Research Fellow to join a project developing and validating deep learning computer vision models to classify mosquito breeding habitat on very high-resolution
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, radiology, pathology, biostatistics, health services research, and health informatics. We provide access to high-performance computing, secure data environments, clinical imaging data, and software tools
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and/or related fields including genetic epidemiology, human genetics, biostatistics, bioinformatics, computational biology, or phenomics (including EHR, deep medical imaging, and biomarker profiling