9 image-computer-engineering Postdoctoral positions at Stanford University in Postdoctoral
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Qualifications: Ph.D. in Computer Science, Electrical Engineering, Biomedical Engineering, Medical Physics, Mathematics, or a related field. Strong publication record and programming skills. Required Application
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(HAI)(link is external) . Research Focus The fellow will lead computational modeling efforts to develop large-scale, multimodal models of the human brain. The work will involve integrating brain imaging
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Posted on Tue, 08/18/2026 - 10:22 Important Info Faculty Sponsor First name: Adam Faculty Sponsor Last Name: Boies Stanford Departments and Centers: Mechanical Engineering Postdoc Appointment Term
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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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intellectual perspectives these backgrounds bring. Prof. Lynette Cegelski is Professor of Chemistry and, by courtesy, of Chemical Engineering at Stanford and is affiliated with the Stanford Biophysics Program
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disorders. Key responsibilities include: (1) Develop and apply computational methods for heart failure discovery. (2) Analyze large-scale human datasets, including imaging, genetics, omics, EHR, and outcomes
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QUALIFICATIONS: PhD in computer science, electrical/biomedical engineering, statistics, applied mathematics, or a related field. Strong track record in machine learning/deep learning with imaging data
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and experimentalists working across species as part of SCENE The Tolias Lab fuses large‑scale systems neuroscience with machine learning to derive principled models of cortical computation. Our newly
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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