Department PPPL Theory
Category Research and Laboratory
Full-Time / Part-Time Full-Time
The Princeton Plasma Physics Laboratory (PPPL) is seeking a highly skilled and experienced computational scientist who will have major technical responsibility for high-performance computing related to porting of PPPL codes to upcoming exascale computers as part of the Exascale Computing Project. In particular, PPPL is seeking a recognized leader and authority in the area of the scalable GPU and C++ computing on extreme scale high-performance computers at DOE facilities.
The successful candidate for this position will have creativity, foresight, and mature professional judgment in anticipating and solving unprecedented computational problems, in determining project objectives and requirements, and in developing standards and guides for diverse software engineering, computing, and scientific activities. The successful candidate will also initiate and maintain extensive contacts with key software engineers and scientists in other areas of the Laboratory and in other organizations and skillfully negotiate critical issues.
The successful candidate will have the following core duties and responsibilities:
- Provide authoritative technical guidance in the application of plasma codes to high performance GPU computers on DOE and PPPL facilities.
- Conceive and plan efforts in broad GPU code-optimization and the relevant library areas of considerable novelty and importance where precedents are lacking.
- Stay abreast of new computational technology or library developments in order to be able to recommend changes in emphasis of computational programs or new programs warranted by such developments.
- Provide timely, accurate, and authoritative advice to other computational physicists who consult with the successful candidate.
The duty will require 51% or higher percentage employment.
Education and Experience:
- At least approximately 5 years of experience in the related field after PhD degree in computational sciences, natural sciences, or engineering.
Knowledge, Skills and Abilities:
- Fluent in the modern parallelization tools such as MPI, OpenMP, CUDA, and OpenACC.
- Proven experience in the large-scale GPU off-loading.
- Demonstrated contributions to techniques that are regarded as advances in the field of extreme-scale computing with GPUs.
- Fluent in the scientific programing languages including Fortran and C++.
- Must be able to show collaborative and leadership experience in the code-performance engineering activities with code authors and other software engineers.
- The job can be performed on-site or off-site.
Princeton University is an Equal Opportunity/Affirmative Action Employer and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law. EEO IS THE LAW
Please be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from participation in certain foreign government talent recruitment programs. All PPPL employees are required to disclose any participation in a foreign government talent recruitment program and may be required to withdraw from such programs to remain employed under the DOE Contract.