Unit: School of Medicine
Department: Cellular, Molecular and Genetic Medicine
Department Summary: The Department of Cellular, Molecular and Genetic Medicine is dedicated to unraveling the fundamental biology that supports health and drives disease. Our faculty, trainees and students tackle some of the most pressing challenges in biomedical science, from the molecular and genetic roots of disease to the complexities of whole-body physiology.
Our foundational studies are driving the frontiers of scientific discovery, pushing the boundaries of what we understand about biology, disease and the human body. From our labs in downtown Richmond to research collaborations around the world, our work is generating new knowledge, influencing the direction of biological science and redefining what is possible in biomedical research.
We are proud to be a community of passionate educators and mentors, deeply committed to empowering the next generation of scientists and leaders. With alumni enjoying successful careers across a broad spectrum of industries, our rigorous training programs offer students a transformative education that drives innovation today and creates lasting impact for tomorrow.
Mission:
The Department of Cellular, Molecular and Genetic Medicine at Virginia Commonwealth University School of Medicine is committed to advancing molecular discovery, disease biology, and translational medicine through innovative research, education, and collaboration. The Division of Biomedical AI within CMGM is being developed to integrate artificial intelligence, machine learning, computational methods, and biomedical data infrastructure with molecular discovery and cancer research.
This position will support highly collaborative research across CMGM, Massey Comprehensive Cancer Center, the School of Medicine, and other VCU research programs. The goal is to strengthen collaborative cancer research through advanced spatial multi-omics analysis, scalable data systems, reproducible computational pipelines, AI-enabled research workflows, and cloud-based biomedical data infrastructure.
Chief Purpose of this Position:
The Department of Cellular, Molecular and Genetic Medicine seeks a full-time, 12-month, non-tenure-track Research Assistant Professor in Biomedical AI, Spatial Multi-Omics, and Cancer Data Science. This is a 100% research position focused on collaborative and team-based biomedical research, with particular emphasis on supporting cancer center projects and translational research programs.
The candidate will bring expertise in spatial multi-omics, database management, data curation and provenance, reproducible pipeline development, AI agent development, and cloud computing. The candidate will work closely with investigators across CMGM, Massey Comprehensive Cancer Center, and the broader School of Medicine to develop, implement, and maintain computational infrastructure for high-impact biomedical and cancer research.
Duties & Responsibilities:
Research: 100%
Contribute to collaborative biomedical and cancer research projects through the development and application of computational methods, data infrastructure, and AI-enabled research workflows.
Responsibilities include developing and maintaining reproducible pipelines for spatial transcriptomics, spatial proteomics, single-cell multi-omics, imaging, and related biomedical data types; designing data management systems that support data curation, metadata tracking, provenance, quality control, and reproducibility; supporting database development and integration for large-scale cancer and molecular medicine datasets; and implementing cloud-based computing workflows for scalable analysis and collaboration.
The candidate will also contribute to AI-enabled research infrastructure, including AI agents for data analysis, workflow automation, documentation, quality control, and reproducible biomedical discovery. The successful candidate will collaborate with faculty, clinicians, trainees, and research staff; contribute to manuscripts, grant applications, presentations, and reports; and help ensure that computational workflows are rigorous, transparent, scalable, and reusable across collaborative research programs.
Qualifications:
Minimum Qualifications
- PhD or equivalent degree in bioinformatics, computational biology, biomedical data science, computer science, biostatistics, statistics, engineering, genomics, cancer biology, or a related field
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