-
for highly motivated postdoctoral candidates with a PhD in bioengineering deep knowledge in computational biology and machine learning. Candidates with a molecular biology or engineering degrees with
-
monitoring systems, bedside monitoring devices, or medical device data. Experience linking physiologic waveform features to clinical outcomes. Experience with machine learning, deep learning, predictive
-
Stanford Departments and Centers: Environmental Social Sciences Postdoc Appointment Term: 12 months renewable for an additional 2 years based on satisfactory performance and availability of funding
-
Pediatrics Postdoc Appointment Term: 2 year Appointment Start Date: Open position How to Submit Application Materials: https://forms.gle/xuUxLuwf4cTcBvWs9(link is external) Does this position pay above the
-
: The candidate must have a PhD and extensive experience in modern deep neural network-based techniques. The ideal candidate should have: A PhD and a strong record of research or applied work in deep learning, with
-
appointed through the Office of Postdoctoral Affairs. The FY27 minimum is $79, 056. Precision mapping of vector borne diseases using deep learning & high resolution remote sensing data Faculty in Stanford
-
imaging, genetics, omics, EHR data, and clinical outcomes. Ongoing work builds on deep-learning phenotypes from cardiovascular imaging at population scale and extends toward myocardial tissue remodeling
-
to appointment start date We welcome candidates with deep expertise in one or more relevant areas, and a strong desire to learn across disciplines: Computational Biology: Spatial/single-cell omics, bioinformatics
-
Postdoc Appointment Term: The initial appointment is 9–12 months (typically 12 months); the second and subsequent years are awarded upon demonstrating satisfactory progress in the first year and assuming
-
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