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The Savic Lab at UCSF is seeking a dynamic and highly skilled Senior Manager, Scientific Publications to join our team. In this role, you will lead the scientific communication strategy for the Savic Integrated Pharmacology Laboratory and the PReDiCTR-TB Consortium, partnering with investigators to develop high-impact manuscripts, grant applications, consortium reports, scientific presentations, and strategic communications that advance model-informed drug development (MIDD), translational pharmacology, quantitative systems pharmacology (QSP), AI-enabled translational science, and global tuberculosis research. As the Senior Manager, Scientific Publications in the Savic Lab, you will play a pivotal role in advancing internationally recognized research programs in model-informed drug development, translational pharmacology, and AI-enabled quantitative science for infectious diseases. You will help shape the scientific voice of the Savic Lab and PReDiCTR-TB through publications, grants, scientific strategy, and international collaborations by ensuring that cutting-edge research is communicated effectively to a broad audience. The work environment is casual; however, professional behavior, rapt attention to detail and the ability to meet deadlines are clear requirements. The candidate must be able to work with prolific, high-energy lead scientists with complex schedule needs. This is a unique opportunity to combine your scientific expertise with strategic communication skills in a collaborative and innovative environment. The Savic Lab is a global leader in model-informed drug development for infectious diseases and serves as a quantitative innovation hub for translational pharmacology, AI-enabled modeling, and next-generation regimen design. The laboratory conducts groundbreaking research across TB, HIV, malaria, pediatric infectious diseases, translational PK/PD, and systems pharmacology. Through its leadership role in PReDiCTR-TB, the lab collaborates with international partners to integrate computational science, mechanistic modeling, and clinical translation into actionable strategies that improve global health outcomes. Through PReDiCTR-TB, the laboratory works with academic, industry, nonprofit, and regulatory collaborators to integrate heterogeneous preclinical and clinical datasets into predictive models that accelerate TB regimen optimization, dose selection, and translational decision-making.