APPLICATION INSTRUCTIONS:

• CURRENT PENN STATE EMPLOYEE (faculty, staff, technical service, or student), please login to Workday to complete the internal application process. Please do not apply here, apply internally through Workday.

• CURRENT PENN STATE STUDENT (not employed previously at the university) and seeking employment with Penn State, please login to Workday to complete the student application process. Please do not apply here, apply internally through Workday.

• If you are NOT a current employee or student, please click “Apply” and complete the application process for external applicants.

 

Approval of remote and hybrid work is not guaranteed regardless of work location. For additional information on remote work at Penn State, see Notice to Out of State Applicants.

This is a term position; length of the term will be discussed during the interview process. Continuation past the term length discussed will be based on university need, performance, and/or availability of funding.

 

POSITION SPECIFICS

The Pennsylvania State University's Department of Civil and Environmental Engineering seeks a Postdoctoral Scholar to participate in a multi-disciplinary, multi-investigator NSF-funded research project. The overarching aim of this project is in the development of new knowledge and a new framework to facilitate the optimal design and life-long adaptation of civil infrastructure systems that rigorously accounts for diverse uncertainties in the life-cycle demands, system's state, and decision criteria. This project thus aims to offer an engineering response to infrastructure adaptation, mitigating the impact of evolving hazards on the built environment and society, and fundamentally transforming the basis for which infrastructure is designed, maintained, and adapted, to ensure a prosperous and sustainable future.

We seek a highly motivated and knowledgeable individual eager to expand their expertise while contributing to the management and execution of research as well as mentoring of graduate students. The required qualifications are:

• PhD degree in mathematics, science, engineering, or a related field by the start date.

• Extensive experience in one or more of the following areas: probabilistic methods, risk and reliability, stochastic control processes, dynamic programing, deep reinforcement learning.

• Strong track record in scientific contributions supported by peer-reviewed publications.

• Strong programming skills including proficiency with Python and Matlab.

• Strong communication and interpersonal skills.

• Knowledge of hydraulics and stochastics in hydraulics, though not required, will be beneficial and considered favorably.

Review of applications will begin immediately and continue until the position is filled. To apply, please submit a single PDF file (5MB max) that includes: a cover letter, a curriculum vitae, and the contact information for two professional references. Review of applications will begin immediately and continue until the position is filled. For questions, please contact Dr. Gordon Warn at