Sr. Scientist, Therapeutics & Translational Bioinformatics

Moderna is seeking a highly motivated and experienced Senior Scientist, Therapeutics & Translational Bioinformatics, to join a multidisciplinary team supporting the discovery and development of mRNA-based therapeutics and vaccines. The role will advance early therapeutic development through computational analysis of human, clinical, and preclinical data while deepening our understanding of mRNA platform immunology through translational studies. This person will apply expertise in computational biology, immunology, machine learning/AI, and advanced statistical methods to identify therapeutic targets, biological mechanisms, biomarkers, response signatures, and patient-level factors that inform program strategy. The successful candidate will have strong hands-on experience with bulk and single-cell transcriptomics and TCR/BCR repertoire analysis, integrated multi-omics, and machine-learning or deep-learning approaches. The person will lead the computational effort for therapeutic or platform programs, partnering with multidisciplinary teams, and external collaborators to define scientific questions, guide study design, lead analyses, and translate biological data into actionable next steps. The successful candidate will be scientifically curious, quantitatively rigorous, comfortable operating in an interdisciplinary and rapidly evolving environment, and motivated by the opportunity to translate complex data into therapeutic impact. Here’s What You’ll Do Lead the computational effort for therapeutic and translational programs, partnering with Research, Translational Medicine, and Clinical Development teams to define computational strategies, data requirements, and analysis plans from discovery through early clinical development. Lead integrated multi-omics analyses of data from human clinical and translational studies, preclinical models, and in vitro experiments to generate system-level biological insights. Perform rigorous bulk and single-cell transcriptomic analyses, including QC, cell-type annotation, differential expression, trajectory inference, cell–cell communication, and cross-study integration. Analyze bulk and single-cell TCR/BCR repertoire data, including clonotype diversity, expansion, convergence, lineage relationships, and associations with cellular phenotypes. Develop or apply machine-learning and deep-learning approaches to high-dimensional biological and clinical data for biomarker discovery, patient stratification, response and safety prediction, disease-state characterization, and therapeutic target prioritization. Analyze and integrate immune-assay data, including flow cytometry, cytokine and chemokine measurements, serology, ELISpot, intracellular cytokine staining, and other immune readouts. Translate computational findings into testable biological hypotheses and actionable recommendations for target and treatment modality selection, indication prioritization, MoA studies, biomarker strategies, patient selection, and study design. Leverage AI tools to develop and maintain scalable, reproducible, and well-documented analytical algorithms and pipelines using modern data science best practices. Clearly communicate findings through presentations, technical reports, publications, study summaries, and regulatory or clinical-development documents. Provide technical leadership and mentorship to junior computational scientists and contribute to the development of shared analytical standards, pipelines, and best practices. Here’s What You’ll Bring to the Table PhD in Computational Immunology, Bioinformatics, Biomedical Engineering, or a related quantitative discipline, with at least 2 years of relevant postdoctoral or industry experience. Strong scientific foundation in both computational biology and immunology, with the ability to connect molecular and cellular findings to immune mechanisms, human disease biology, and therapeutic development. Demonstrated experience applying computational analyses