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for diverse applications in biomedical informatics (e.g., classifying patient outcomes in multiple domains, outcome prediction of treatment based on EHR) Work with large-scale biomedical datasets (e.g
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sensor integration. Strong coding and debugging skills. Excellent communication, documentation capabilities and a demonstrated track record of publication. An enthusiasm for developing new measurements
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human samples collected by our clinical colleagues from patients, mouse models, primary explants, and organoid cultures. Our group collaborates with multiple departments at Stanford and beyond
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accomplishments, (b) Your broader research interests, and (c) why you are interested in working with us A sample of data analysis code (published or unpublished) A representative writing sample (published
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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
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development and in the adult. Our research is directed at neuroprotection and regeneration of retinal ganglion cells and the optic nerve, a major unmet need in glaucoma and other optic neuropathies. Multiple
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glioma models to investigate novel therapeutic strategies and radiation. The goal is to explore a paradigm shift from the somatic mutation theory of cancer to a wound-healing and metabolic reprogramming
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-author manuscript with related analysis code and references later during the recruitment process. Stanford is an equal opportunity employer and all qualified applicants will receive consideration without
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Qualifications: • Doctoral degree with quantitative training (ideally in econometrics) or relevant research experience. • Strong coding skills in R, Stata, or other statistical software package. • Good
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Experience in R, python or another scientific programming language Experience collaborating on and documenting, sharing, and managing code with version control Leadership experience Required Qualifications