The Atlanta VA Medical Center (VAMC) Research Service seeks an outstanding investigator with expertise in advanced artificial intelligence methods to support and advance VA research focused on cancer detection, prognosis, treatment selection, and survivorship. The investigator will work in a multidisciplinary VA research environment and collaborate with computational scientists, oncologists, radiologists, pathologists, and other clinical and research professionals. This position offers an exceptional opportunity to generate and translate practice-changing evidence on the responsible use of AI in oncology within the Veterans Health Administration (VHA), the nation's largest integrated health system. The work will focus on improving outcomes, reducing disparities, and enhancing patient safety for Veterans, including those affected by tobacco-, environmental-, and service-related cancer risks. About the Opportunity The successful candidate will lead or co-lead collaborative, innovative research applying AI to Veteran cancer care. Potential areas of research include: Radiopathomics: computational fusion of CT/MRI radiomics with digital pathology (H&E whole-slide) features to predict prognosis and treatment response in non-small cell and small cell lung cancer, prostate cancer, and other Veteran-prevalent malignancies. Computational pathology of the tumor microenvironment, including tumor-infiltrating lymphocyte architecture, vascular and stromal/collagen organization, and immune-cell spatial patterning, as prognostic and predictive biomarkers. Radiogenomics and multimodal data integration (clinical, imaging, pathology, and molecular/genomic) to improve cancer phenotyping, risk stratification, and prediction of response to immunotherapy and chemotherapy. AI-driven imaging biomarker development leveraging national data infrastructure such as the Medical Imaging and Data Resource Center (MIDRC), with an eye toward validation in VA's Corporate Data Warehouse (CDW), VA Science and Data Platform (SDP), and the Million Veteran Program (MVP). Emerging approaches involving agentic AI and foundation models for contextualized, multimodal cancer decision support and the development of interpretable clinical AI tools. AI for cancer research and care delivery is a strategic priority for the Atlanta VAMC and the VA Office of Research and Development nationally, with growing emphasis on responsible, real-world implementation across the VA health care system. This work is well suited for external funding from federal agencies and other research sponsors, and the successful candidate will be positioned to translate advanced AI methods into pragmatic, implementation-focused research that benefits Veterans nationwide. VA Research Environment This role is embedded within the Atlanta VAMC Research Service and supports a broad portfolio of collaborative research addressing high-priority health concerns affecting Veterans. The research environment brings together investigators, clinicians, data scientists, and research staff with expertise in cancer, medical imaging, digital pathology, precision medicine, and health care delivery. The successful candidate will benefit from access to VA research resources, relevant clinical and imaging data, established computational capabilities, and close collaboration with VA clinical and research leadership. Opportunities may also include participation in multidisciplinary clinical conferences, national VA research collaborations, and projects using VA data platforms and other approved research infrastructure. Strategic Impact This recruitment will strengthen the Atlanta VA's capacity for AI-enabled precision oncology research and implementation science. The position will help advance the development and evaluation of radiopathomic and multimodal AI approaches for Veteran cancer screening, diagnosis, prognosis, and treatment; support the responsible integration of research findings into VA care; and contribute to equitable, evidence-based cancer care for Veterans, including those affected by service-related and environmental exposures.
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Job Type
Full-time
Career Level
Senior
Education Level
Ph.D. or professional degree