Assistant Professor - Division of Biomedical AI, Cellular, Molecular and Genetic Medicine

The Department of Cellular, Molecular and Genetic Medicine (CMGM) 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 department brings together expertise in cellular biology, molecular mechanisms, genetics, genomics, computational biology, and disease-focused discovery to address major challenges in human health.

The Division of Biomedical AI within CMGM is being developed to integrate artificial intelligence, machine learning, and advanced computational methods with molecular discovery and biomedical research. The division will focus on developing AI-driven approaches that connect molecular and cellular mechanisms with disease modeling, therapeutic discovery, cancer biology, and precision medicine. A major goal of the division is to build highly collaborative research programs that bridge computational innovation with biological and translational discovery across CMGM, the School of Medicine, Massey Comprehensive Cancer Center, the Wright Center for Clinical and Translational Research, and other VCU research programs.

The Department of Cellular, Molecular and Genetic Medicine seeks to recruit two junior faculty members (tenure eligible) at the rank of Assistant Professor in Biomedical AI and Computational Molecular Medicine. Successful candidates will develop independent, externally funded research programs that apply innovative artificial intelligence, machine learning, computational biology, and/or quantitative modeling approaches to important problems in molecular medicine.

We are particularly interested in candidates whose research aligns with one or more of the following priority areas:

Candidates developing biomedical foundation models and AI-driven virtual cell, virtual tissue, and digital twin approaches that integrate single-cell, spatial, imaging, perturbation, and multi-omics data to model molecular programs, cellular states, tissue organization, disease progression, and therapeutic response.

Candidates developing AI approaches for cancer research, tumor microenvironment modeling, spatial and single-cell analysis of cancer ecosystems, therapeutic response prediction, target discovery, and AI-enabled drug discovery.

Candidates developing causal, perturbational, and mechanistic AI approaches for biomarker discovery, therapeutic target prioritization, treatment-response prediction, and identification of disease-driving molecular or cellular programs.

Candidates working in other innovative areas of artificial intelligence research in the biomedical domain are also encouraged to apply, particularly those whose work can advance digital pathology, molecular discovery, disease biology, translational medicine, therapeutic discovery, precision medicine, or precision health.

Successful candidates will be expected to contribute to the growth of the Division of Biomedical AI within CMGM and to work collaboratively with investigators across CMGM, the broader School of Medicine, Massey Comprehensive Cancer Center, the Wright Center for Clinical and Translational Research, and other VCU programs. The positions offer substantial opportunities to collaborate with disease-focused, translational, and clinical research programs, including cancer research, clinical and translational science, molecular medicine, immunology, genomics, therapeutic discovery, and other areas of biomedical discovery.

Minimum Qualifications

• →PhD, MD/PhD, or equivalent doctoral degree in computer science, computational biology, biomedical data science, bioinformatics, biostatistics, statistics, or a related field
• →Evidence of strong research productivity and potential to develop an independent, externally funded research program
• →Expertise in artificial intelligence, machine learning, computational biology, quantitative modeling, or related computational methods relevant to molecular medicine
• →Demonstrated ability or strong potential to work as a highly collaborative researcher within multidisciplinary biomedical research teams
• →Strong interest in collaborating with investigators in CMGM, Massey Comprehensive Cancer Center, the Wright Center for Clinical and Translational Research, and the broader School of Medicine
• →Demonstrated ability to work in and foster an environment of respect, professionalism, and civility with a population of faculty, staff, and students from all backgrounds and experiences, or a commitment to do so as a faculty member at VCU

Preferred Qualifications

• →Biomedical foundation models trained on single-cell, spatial, multi-omics, imaging, perturbation, or molecular datasets
• →Virtual cells, virtual tissues, molecular/cellular/tissue-level digital twins, or mechanistic models of disease progression and therapeutic response
• →Multimodal AI for integrating genomics, transcriptomics, epigenomics, proteomics, metabolomics, spatial omics, pathology imaging, and clinical or phenotypic data
• →AI for cancer research, including tumor microenvironment modeling, cancer ecosystems, spatial tumor biology, immune-tumor interactions, therapeutic resistance, and treatment-response prediction
• →AI-enabled drug discovery, therapeutic target discovery, molecular design, perturbational modeling, and computational prioritization of therapeutic interventions
• →Causal, perturbational, and mechanistic AI for biomarker discovery, therapeutic target prioritization, treatment-response prediction, and identification of disease-driving molecular or cellular programs
• →AI for tissue architecture, cellular neighborhoods, microenvironmental organization, disease ecosystems, and molecular mechanisms of disease
• →Other innovative AI approaches in the biomedical domain that advance molecular discovery, disease modeling, translational medicine, cancer research, therapeutic discovery, precision medicine, or precision health
• →Development of reproducible computational pipelines, scalable AI systems, and software tools using Python, R, Julia, or related computational languages
• →Experience with high-performance computing, cloud computing, GPU-based AI/ML workflows, or large-scale biomedical data infrastructure
• →Strong potential for collaboration with disease-focused research programs in cancer, immunology, cardiovascular disease, metabolic disease, neuroscience, rare diseases, or other areas of molecular medicine

Applicants should submit a curriculum vitae, research statement, teaching and mentoring statement, and names of references. Review of applications will begin October 1, 2026 and continue until the positions are filled.