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Division of Engineering and Applied Science

Postdoctoral Scholars - Data Assimilation, Inverse Problems and Scientific Machine Learning

Applications Due:
December 1, 2022


The positions are funded through a Department of Defense Vannevar Bush Faculty Fellowship held by Prof. Andrew Stuart in the Computing and Mathematical Sciences Department, within the Division of Engineering and Applied Sciences, at Caltech. Postdoctoral scholars working in the three areas of Data Assimilation, Inverse Problems and Scientific Machine Learning, or at the intersection of these three areas, are sought; researchers in both the mathematical and computational aspects of these disciplines will be considered. Areas of emphasis for the research program include, but are not limited to, approximation theory, computational science and engineering, ensemble Kalman methods, nonlinear filtering, numerical analysis of partial differential equations, statistical learning, stochastic and random differential equations and stochastic processes.

The proposed work addresses the need for a mathematical framework underpinning the analysis and development of model-centric and data-informed predictive computational science and engineering; this will allow for the integration of centuries of mathematical modeling experience, decades of computational modeling experience, and recent innovations in algorithms, computer design and hardware stemming from the current revolution in the data sciences. Creating this framework requires a new theory at the interfaces of machine learning, numerical analysis and statistics. The proposed research will address this problem in the specific setting of the learning of mappings between spaces of functions -- operator learning.

The goal of the proposed research is to develop the mathematical framework needed for algorithms that accelerate execution of black box computer code, by means of a data-informed surrogate, as is crucial to the solution of large-scale inverse problems; or algorithms that discover a structured computational model when a first principles model is not available, as often arises for cyber-physical systems or in data-assimilation. The mathematical framework will be developed in tandem with applications in science and engineering.

For more information about the proposed research please contact Professor Andrew Stuart.

As minimum qualification, you are expected to have completed a doctoral degree in applied mathematics, computer science, engineering, physics, statistics or a related field at the time of the appointment; to have a strong mathematical, and/or computational background; and to have demonstrated effective written and verbal communication skills.

Applications comprising a curriculum vitae, a one-page statement of research interests, and three letters of recommendation should be submitted online. Application files will be reviewed starting December 1st 2022.

If there are any questions concerning the application process, please contact Jolene Brink.

Instructions for Applicants

  1. Create an account.
  2. Fill out the application form.
  3. After you submit your application form send the link that is provided to your three references and have them upload their letters of recommendation.
  4. Upload the following documents (as individual files or in one combined pdf):
    • curriculum vitae;
    • a one-page statement of research interests.

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity, or national origin, disability status, protected veteran status, or any other characteristic protected by law.

Postdoctoral positions are term appointments with specific renewal requirements.

Caltech has implemented a mandatory vaccination policy effective October 15, 2021, requiring COVID-19 vaccinations for all employees (with Institute-approved exemptions for religious or medical contraindications only). At present, an individual is deemed “fully vaccinated” when that person has received, at least 14 days prior, either the second dose in a two-dose COVID-19 vaccine series (e.g., Pfizer or Moderna) or a single-dose COVID-19 vaccine (e.g., Johnson & Johnson). Upon eligibility, employees are required to receive the COVID-19 booster as part of the vaccine mandate. As a condition of employment, employees must submit official COVID-19 vaccine documentation. More information may be found here.