UNIV - Open Rank - Department of Pharmacology and Immunology at Medical University of South Carolina Medical Center in Charleston

Job description

Job Description Summary 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. Entity Medical University of South Carolina (MUSC - Univ) Worker Type Employee Worker Sub-Type​ Faculty Cost Center CC001032 COM PHARM Administration CC Pay Rate Type Salary Pay Grade University-00 Pay Range 0.00 - 0.00 - 0.000 Scheduled Weekly Hours 40 Work Shift Job Description Faculty Position in Computational Biology and Bioinformatics Department of Pharmacology and Immunology, Medical University of South Carolina (MUSC), Charleston, South Carolina 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. Environment The Department of Pharmacology and Immunology provides a collaborative and rapidly growing research environment with strengths spanning immunology, molecular pharmacology, cancer biology, and translational biomedical science . The department is committed to integrating data-driven discovery with mechanistic biology to advance therapeutic development. The department hosts internationally recognized laboratories working on translational and clinical multiomic spatialomics by mass spectrometry imaging integrating transcriptomics with metabolomics, lipidomics, glycomics and proteomics centered on immunology and therapeutics. The department boasts a state-of-the-art proteomics core integrative with multiomic metabolomic capabilities. MUSC offers extensive opportunities for interdisciplinary collaboration through institutional programs in precision medicine, cancer research, genomics, bioinformatics, and clinical a