The School of Computer Science at the University of Oklahoma invites applications for a 12-month non-tenure track Research Assistant Professor position in Computer Science with a focus on informatics and AI/ML for medical imaging in translational cancer research. This Research Assistant Professor will be part of the Clinical Imaging and Data Resources Core (CIDRC) of the
NIH COBRE
Oklahoma Center of Medical Imaging for Translational Cancer Research (OCMICR). The position will perform independent and collaborative research in medical imaging AI and informatics, including image segmentation, representation learning, multimodal data integration, quantitative imaging biomarkers, AI-assisted annotation, and reproducible computational analysis. Responsibilities The successful candidate will be expected to: Conduct methodological and collaborative research in areas such as medical image segmentation, classification, registration, multimodal learning, radiomics/pathomics, AI-assisted annotation, foundation models, and quantitative imaging biomarker discovery; Collaborate with investigators on the design and analysis of cancer imaging studies involving radiology, pathology, microscopy, optical imaging, ultrasound/photoacoustic imaging, and other biomedical imaging modalities; Support the development of imaging informatics and computational infrastructure for organizing, processing, analyzing, and sharing multimodal imaging datasets; Develop reproducible computational workflows for image preprocessing, feature extraction, model training, evaluation, visualization, and downstream statistical or machine learning analysis; Integrate imaging data with relevant clinical, biospecimen, biomarker, molecular, or other biomedical data to support translational interpretation; Contribute to manuscripts, grant applications, preliminary-data generation, software development, documentation, and training activities; Participate in interdisciplinary consultations, workshops, and collaborative research activities related to CIDRC and the broader medical imaging research community
Qualifications:
A Ph. D. in Computer Science, Data Science, Biomedical Informatics, Electrical Engineering, or a closely related field. Demonstrated research expertise in one or more of the following areas: machine learning, computer vision, medical image analysis, or biomedical imaging informatics. A record of scholarly productivity appropriate for appointment at the rank of Research Assistant Professor. Strong programming, system-building, and experimental evaluation skills. Ability to develop, validate, and apply computational methods for biomedical imaging data. Ability to work effectively in interdisciplinary research teams involving clinicians, biomedical engineers, biostatisticians, and cancer researchers. Excellent written and oral communication skills.
