RTP - Research Fellow - AI and Informatics

A Research Fellow opportunity is available under the mentorship of Hao Gong, Ph.D. in the Research Department of AI and Informatics.

A Research Fellow in Engineering in this role will apply advanced computational and engineering skills to the development, implementation, and evaluation of AI / ML algorithms for clinical applications. Responsibilities include processing and analyzing imaging and multimodal clinical data, implementing and testing of computational models, and supporting translational research and clinical deployment within an interdisciplinary environment.

A Research Fellow at Mayo Clinic is a temporary position intended to provide training and education in research. Individuals will train in the research program of a Mayo Clinic principal investigator. Qualified individuals will demonstrate the potential for research as evidenced by their training and peer-reviewed publications and should become competitive for national research grants. Proof of English proficiency is required for J-1 Short-Term Scholars, Research Scholars, Professors, Specialists, and Student Interns sponsored by Mayo Clinic.

The Research Fellow will lead the development and validation of advanced AI / ML algorithms to support diagnosis and treatment planning, work closely with clinical collaborators to translate in-house-developed techniques toward clinical adoption, and disseminate significant scientific findings through conference presentations and peer-reviewed publications. Applicants should have a strong background in clinical image processing and analysis, generative modeling, multi-modal learning, experimental design, and statistical evaluation. Additional domain knowledge in clinical imaging physics or computational biology is considered a plus.

• Ph.D. degree in Computer Science, Electrical and Computer Engineering, Biomedical Engineering, Applied Mathematics, Medical Physics, or a related field.
• Extensive expertise in developing advanced AI / ML methods for clinical imaging tasks, such as disease classification, lesion detection, lesion / tumor segmentation, and biomarker analysis.
• Proven, hands-on experience with generative modeling approaches (e.g., GAN, Diffusion, or LLM).
• Experience of designing or implementing multi-modal frameworks that integrate imaging data with other modalities (e.g., EHRs, genomics, clinical reports).
• Excellent Python programming skills are required, with proficiency in TensorFlow / PyTorch and modern ML tools.
• (Preferred) Experience with scalable computing, such as multi-GPU training, distributed data processing, and research-oriented MLOps.
• Excellent oral and written English communication skills, along with a solid record of peer-reviewed publications in relevant conferences and academic journals.
• The ability to work independently and collaboratively within a multidisciplinary environment.