The Department of Pharmacology and Immunology at the Medical University of South Carolina (MUSC) invites applications for a tenure-track faculty position in Computational Biology, Bioinformatics, or Systems Biology at the rank of Assistant or Associate Professor. Exceptional candidates with a strong record of innovation and productivity will be considered. We seek a scientist who develops and applies advanced computational, statistical, and data science approaches to address fundamental and translational questions at the interface of pharmacology and immunology. The successful candidate will leverage large-scale biological data to advance mechanistic understanding of immune regulation, drug responses, and disease pathogenesis, while contributing to the development of next-generation therapeutic strategies. Areas of interest include, but are not limited to: Computational and systems immunology, Single-cell, spatial, and multi-omics data analysis, Systems pharmacology and drug response modeling, Machine learning and AI approaches in biomedical research, Computational approaches to immune-mediated diseases, cancer immunology, or host–pathogen interactions, Integrative analysis linking molecular mechanisms to therapeutic response or precision medicine. The department is particularly interested in candidates who will bridge computational discovery with experimental and translational research programs in pharmacology and immunology. Faculty in the department study immune signaling, inflammation, cancer biology, host–pathogen interactions, neuroimmunology, and therapeutic target discovery, providing strong opportunities for collaborative team science. The successful candidate will be expected to establish an independent, externally funded research program, contribute to interdisciplinary collaborations, and participate in the teaching and mentoring missions of the department, including graduate education. The successful candidate will also have opportunities to contribute to the department’s vision of building a data-driven research ecosystem that integrates computational modeling, systems biology, and experimental discovery to accelerate therapeutic innovation in pharmacology and immunology.
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Job Type
Full-time
Career Level
Entry Level
Education Level
Ph.D. or professional degree