Vir integrates diverse innovations in science, technology, and medicine to transform the care of people with serious infectious diseases. Vir is taking a multi-program, multi-platform approach to applying these breakthroughs, including the development of treatments that induce protective and therapeutic immune responses. Vir’s scale and scope together with leading scientific and management expertise, allow it to perform significant internal R&D, in license or acquire innovative technology platforms and assets, and fund targeted academic research.
Vir Biotechnology (Vir), a San Francisco based company focused on infectious disease, is establishing a subsidiary to act as a center of excellence for applying cutting edge data science and informatics techniques to accelerate the development of novel pharmaceutical products. This subsidiary is building a team to develop and analyze integrative physiology models and apply those models to complex research and business problems. We seek a Modeling and Simulation Engineer/Scientist to develop and analyze such mechanistic models, with a focus on enumerating causal hypotheses that explain complex phenotypic data.
Engage with research, translational medicine, and clinical development staff to survey, organize, and codify disease phenotype and mechanism data, from literature to laboratory experimental results to clinical patient data.
Work with data scientists to interpret multivariate data patterns, produced by correlative analytics and machine learning algorithms, for their possible causal significance.
Collaborate with project management staff to design modeling scope and detail constrained to project timelines and decision points.
Develop integrative physiology models, maintaining rigorous audit trail of data used in their development.
Apply model-based analyses to the identification and evaluation of drug target and biomarker candidates, optimization of therapies and combinations, and the design and analysis of in vitro and in vivo experiments and clinical trials.
Participate in ongoing refinement and acquisition of software tools to support model development and analysis.
QUALIFICATIONS AND EXPERIENCE:
Minimum 5 years’ experience in developing biological models; biopharma experience a plus.
Expertise in nonlinear ODEs, Bayesian methods, and parameter estimation methods.
Experience in multisystem physiology modeling (beyond pathway or single-cell modeling) and/or Quantitative systems pharmacology (QSP) a plus.
Demonstrated ability in deducing innovative causal hypotheses from disparate data sources.
Strong verbal and written communication skills.
Experience working in cross-disciplinary teams, with formal project management processes, and managing personal time across technical and organizational responsibilities.
Experience with innate and adaptive immunology highly desired.
Experience with decision analysis a plus.
Advanced degree in (Master's Degree of PhD) in engineering, data science, decision analytics, or related discipline.