The Argonne Leadership Computing Facility (ALCF) has an immediate opening for a postdoctoral researcher to work on novel data-driven scientific discoveries for chemistry research targeting our forthcoming exascale supercomputer, Aurora. The ALCF enables breakthroughs in science and engineering by providing supercomputing resources and expertise to the research community.
You will collaborate with scientists in the Early Science Program (ESP) to solve some of the most challenging scientific problems on Argonne’s upcoming Exascale supercomputer, Aurora, to be deployed in 2022. The successful candidate will work with an inter-disciplinary team of scientists to develop data-driven simulation techniques to explore potential energy surfaces for catalytic reactions on noble metal and other simple metal surfaces. You will work in a multi-disciplinary and collaborative environment consisting of computational scientists, computational chemists, electronic structure software developers, computer scientists, applied mathematicians, and machine learning experts.
In this role you will:
- Research and develop novel high-throughput workflows to effectively scale potential energy surface exploration on supercomputers.
- Optimize and refactor existing scientific workflows to reduce latencies that preclude scaling workflows on supercomputers.
- Explore the use of scientific ML methods to improve the efficiency and reliability (i.e. uncertainty quantification) of the scientific workflows.
- Work with software developers to help improve the efficiency and functionality in hardware accelerators, such as GPU and many-core, of the band structure code and new many-body electronic structure methods being developed in NWChemEx for use in chemistry and materials sciences workflows.
- A PhD + 0-3 years in computational sciences including chemistry, computer science, physics, biology, or in a related field.
- Comprehensive experience programming in one or more programming languages such as C, C++, Julia, and Python.
- Knowledge of numerical methods, parallel programming, and developing scientific workflows on HPC resources.
- Knowledge of parallel algorithms, distributed memory architectures, and parallel performance evaluation of domain specific implementations.
- Ability to create, maintain, and support high-quality software.
- An ideal candidate would have published their scientific software in a public repository (e.g. GitHub)]
- Strong communication skills both verbal and written.
- Independent judgment and critical thinking.
As an equal employment opportunity and affirmative action employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a diverse and inclusive workplace that fosters collaborative scientific discovery and innovation. In support of this commitment, Argonne encourages minorities, women, veterans and individuals with disabilities to apply for employment. Argonne considers all qualified applicants for employment without regard to age, ancestry, citizenship status, color, disability, gender, gender identity, gender expression, genetic information, marital status, national origin, pregnancy, race, religion, sexual orientation, veteran status or any other characteristic protected by law.
Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne's Legal Department.
All Argonne offers of employment are contingent upon a background check that includes an assessment of criminal conviction history conducted on an individualized and case-by-case basis. Please be advised that Argonne positions require upon hire (or may require in the future) for the individual be to obtain a government access authorization that involves additional background check requirements. Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment.