![]() A successful candidate will be expected to obtain substantial grant funding (e.g., NIH award(s)). The ideal candidate will have potential trajectory and/or demonstrated breadth of preparation, as exemplified by significant research experience resulting in high impact publications in computational oncology. The successful applicant will spend the majority of time on their independent research program and approximately 25% on collaborating with members of the Division and Department to support computational biology and bioinformatics needs. Applicants should also have expertise in development and application of machine learning/artificial intelligence approaches for translational cancer research and demonstrated prior substantial scholarly contributions in these areas.Īpplicants must have an interest in leading an independent research program and have the desire to closely collaborate with other investigators in the Division and Department. and postdoc in the area of computational oncology. radiation biology, treatment response prediction, cancer immunology, cancer detection, etc.). We seek applicants committed to developing an academic program focused on computational oncology in areas relevant to the field of radiation therapy (e.g. to join the Department as an Assistant Professor in the Non-Tenure Line (Research). The Division of Radiation and Cancer Biology in the Department of Radiation Oncology at Stanford University seeks a Ph.D. Stanford University Division of Radiation Biology
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