Research Scientist - Biomedical Informatics

We are seeking a highly innovative Research Scientist to lead the development of AI computational frameworks for modeling complex biological systems using large-scale single-cell and spatial multi-omics data. This position goes beyond conventional bioinformatics analysis and focuses on methodological innovation at the interface of AI, systems biology, and cancer research, including foundation models, graph-based learning, and mechanistic modeling. The successful candidate will drive independent research programs, develop novel computational methodologies, and contribute to high-impact publications and grant proposals. Key Responsibilities Developing AI-based modeling frameworks to simulate complex cancer systems across multiple scales, and develop scalable and reusable computational frameworks and analytical pipelines for multi-omics and spatial data analysis. Ability to construct computational models for senescence and aging dynamics using multi-scale and data-driven approaches. Advanced capability in multi-modal data integration and representation learning across heterogeneous biological datasets. Experience in designing algorithms that leverage single-cell and multi-omics data to guide precision therapeutics, and link molecular mechanisms to phenotypic outcomes (e.g., metastasis, immunotherapy response). Lead independent and collaborative research programs from conception to publication, driving end-to-end project execution. Define scientific questions and computational strategies in collaboration with experimental and clinical teams. Contribute to shaping the long-term computational research direction and scientific vision of the group. Contribute to grant writing (e.g., NIH, NSF), including methodological design, hypothesis development, and preliminary data generation. Mentor junior trainees in computational biology and AI methods. Required Qualifications Ph.D. in Computational Biology, Mathematics, Computer Science, or a related field Demonstrated ability to lead independent research projects beyond doctoral training, and evidence of leadership in collaborative research projects and contributions to grant development Strong track record of methodological research and peer-reviewed publications Postdoctoral research experience (typically >=3 years) or equivalent advanced research training Substantial expertise in deep learning and foundation models, particularly graph representation models, as well as single-cell and spatial omics data analysis and algorithm/model development for biological systems Application Instructions Interested candidates should submit an application including a cover letter, resume, and contact information for three professional references through Workday. Screen reader users may encounter difficulty with the online application. For assistance with applying, please contact View email address on click.appcast.io. If you have questions while submitting an application, please review these frequently asked questions. Final candidates are subject to successful completion of a background check. A drug screen or physical may be required during the post offer process. The university is an equal opportunity employer, including veterans and disability. Thank you for your interest in working at Ohio State. #J-18808-Ljbffr Wexner Medical Center