55 channel-coding-electrical-engineering Postdoctoral positions at Stanford University
Sort by
Refine Your Search
-
external) Candidates from a diverse background are encouraged to apply. The applicant may hold a PhD either in physical sciences/engineering with a strong interest in translational research and motivation
-
decisions are made under pressure, and how technology can support (rather than hinder) patient care. The postdoctoral scholar will use modern data science tools and cloud computing to analyze high-dimensional
-
with electronic health record (EHR) and/or clinical data. Proficiency in Python, with strong coding and debugging skills. Experience with deep learning frameworks such as PyTorch, JAX, TensorFlow
-
autonomy Work with patient electronic health records (EHRs) Interest in equity, bias, and representation in both evaluating the skews of datasets and the implementation of new technology tools
-
lab meetings, journal clubs, and collaborations Required Qualifications: M.D. or Ph.D. in Neuroscience, Cancer Biology, Biomedical Engineering, Electrical Engineering, Radiology, or a related field
-
scientific research on computational linguistics, machine learning, practical applications of human language technology, and interdisciplinary work in computational social science and cognitive science. The
-
fleet, and vendor collaboration with GE Healthcare. Personal ideas and collaborations with other groups in the Stanford Radiologic Sciences Lab are encouraged. Current collaborators include Dan Ennis
-
algorithmic performance. For instance, the scheduling problems that an electric grid operator faces will change daily, but not drastically: although demand will vary, the network structure will remain largely
-
computer science, earth systems science, economics, engineering, health policy, political science, and sociology—to pursue policy-relevant research on topics related to international development and poverty
-
, Outpatient, Carrier, TAF). Develop reproducible code and workflows for data cleaning, linkage, and analysis within Stanford’s secure computing environment. Collaborate with multidisciplinary teams