Job Information
Pacific Northwest National Laboratory Mathematician in RICHLAND, Washington
Organization and Job ID
Job ID: 311863
Directorate: Physical & Computational Sciences
Division: Advanced Computing, Mathematics, and Data
Group: Computational Mathematics
Job Description
Pacific Northwest National Laboratory (PNNL) is a world-class research institution powered by a highly educated, diverse workforce committed to collaboration and work-life balance. We are seeking an early career Applied Mathematician to contribute to our Computational Mathematics group research effort in scientific computing. This is an excellent opportunity to develop your scientific career by joining an interdisciplinary research team that focuses on accelerating scientific discovery through the targeted use of computing. The primary emphasis of this position will be on growing existing and developing new capabilities in the areas of multiscale modeling, uncertainty quantification, inverse problems, and machine-learning methods. Duties include:
Develop and conduct independent research and collaborate with other team members.
Establish technical reputation in professional community including professional societies, other laboratories, academia, and industry.
Mentor and train junior level researchers.
Minimum Qualifications
BA with 2 years of experience, MS/MA with 0-2 years of experience, PhD with 0 years of experience.
Preferred Qualifications
PhD in Applied Mathematics (or related areas) with two years or more of postdoctoral experience.
Experience in writing and leading research proposals.
Experience supervising and mentoring graduate students, postdocs, or junior scientists.
Demonstrated expertise in at least one technical area. Examples include:
Multiscale modeling: Model, analyze and simulate complex systems, including model reduction, multiscale expansion, and renormalization approaches.
Uncertainty quantification: Develop methods to quantify and reduce uncertainty in forward and inverse problems, including Monte Carlo, functional expansion, and Bayesian approaches.
Machine learning: Advance physics-informed machine learning, including approaches based on dynamical systems, statistics, and optimization.
High performance computing: Design and implement methods for large-scale applications, including heterogeneous and edge computing approaches.
Equal Employment Opportunity
Battelle Memorial Institute (BMI) at Pacific Northwest National Laboratory (PNNL) is an Affirmative Action/Equal Opportunity Employer and supports diversity in the workplace. All employment decisions are made without regard to race, color, religion, sex, national origin, age, disability, veteran status, marital or family status, sexual orientation, gender identity, or genetic information. All BMI staff must be able to demonstrate the legal right to work in the United States. BMI is an E-Verify employer. Learn more at jobs.pnnl.gov.
If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via https://jobs.pnnl.gov/help.stm
Please be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from having any affiliation with the foreign government of a country DOE has identified as a “country of risk” without explicit approval by DOE and Battelle. If you are offered a position at PNNL and currently have any affiliation with the government of one of these countries you will be required to disclose this information and recuse yourself of that affiliation or receive approval from DOE and Battelle prior to your first day of employment.
Directorate: Physical & Computational Sci's
Job Category: Scientists/Scientific Support
Group: Computational Math Group
Opening Date: 2021-03-24
Closing Date: 2021-04-14