Associate Research Scientist in Applied Mathematics / Scientific Computing

We are inviting applications for an associate research scientist position in applied mathematics and scientific computing, with an emphasis on inverse problems in seismology and Bayesian analysis. The position is associated with the Modeling Earth from Atomic to Global Scale (MINERALS) project funded by the Gordon and Betty Moore Foundation. The project aims to advance and integrate three branches of geophysics—mineral physics, seismology, and geodynamics—to analyze and interpret the deep‑Earth seismological structure. The successful candidate will work in a multidisciplinary team of senior and junior scientists to develop machine learning and Bayesian methods to interpret seismic tomographic models of the elastic structure of the deep Earth in terms of temperature and mineralogy. Using thermodynamic properties databases, these analytical methods will also be applied to predict equilibrium mineral assemblages in collaboration with an international team of geochemists and petrologists. The position is initially for one year, possibly extending to three years. The position is available immediately and will remain open until filled. Applicants should send a CV, three letters of recommendation, and a cover letter that includes a research statement summarizing their past experience and future goals. Applications should be submitted through the Columbia Interfolio website. Candidates must have a PhD in scientific computing, applied math, mineral physics, geophysics, or materials science with a minimum of 2 years of relevant post‑PhD experience. Salary starting at $79,327. Columbia University is an Equal Opportunity Employer / Disability / Veteran Pay Transparency Disclosure The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training. The above hiring range represents the University?s good faith and reasonable estimate of the range of possible compensation at the time of posting. #J-18808-Ljbffr Columbia University