The Water Institute (https://globalfutures.asu.edu/global-water-institute/) at Arizona State University (ASU) is seeking two Postdoctoral Research Scholars to consider weather modification by optimal chaos control.

This exciting opportunity is for an innovative person(s) who would like to be one of the first to consider how storm trajectories could be "controlled" by small perturbations, leveraging the inherent sensitivity to initial conditions of the nonlinear dynamics of the atmosphere. We are interested in the integrated application of deep learning-based emulators of atmospheric dynamics, and modern data assimilation tools with models for stochastic optimal control to shape the trajectories of coherent Lagrangian structures such as atmospheric rivers, or hurricane tracks. The intention is to build a targeted, new generation modeling system for this express purpose, demonstrate its efficacy and set the stage for the identification of the technical means of providing the perturbations, and the associated physical experiments.

This is a benefits-eligible, full-time, 12-month position, with no tenure implications. The initial appointment will be for one year, with the opportunity for renewal contingent on funding availability and satisfactory performance. The anticipated start date is January 6, 2025 (later date is negotiable).

Essential Duties:

• Develop and implement a modeling strategy for perturbing atmospheric rivers.

• Work with Phd students and interns to explore research tasks related to the project, including guidance on method selection and interpretation.

• Assist with long-term data acquisition, management and archiving.

• Prepare reports, academic/public presentations, and manuscripts for peer-reviewed publications.

Required:

• Applicants must have a recent Ph.D. (within the past four years) in Physics, Mathematics, Nonlinear Science, Complex Systems, Atmospheric Science, Climate Dynamics or other related fields.

• Background in nonlinear dynamical systems, from a physics and mathematics perspective.

• Keen interest in developing technologies that could shape how humanity addresses extreme climate threats in the 21st century.

Desired:

• Demonstrated experience with major climate data sets and processing.

• Demonstrated experience with leading edge deep learning tools, including transformers.

• Demonstrated experience with optimal control and data assimilation algorithms.

The initial deadline for accepting applications is December 2, 2024. If not filled, reviews will occur every week thereafter until the search is closed. Only electronic submissions will be reviewed. Incomplete applications will not be considered.

• Letter of interest outlining qualifications and experience as it relates to this position.
• A complete curriculum vitae.
• The names and contact information of three references (name, position, title, organization, email, and phone number).