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Postdoc - Computational Chemistry and Materials ... (No replies)
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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 a multi-disciplinary team of scientists to develop data-driven simulation techniques to explore potential energy surfaces (PES) for catalytic reactions on noble metal and other simple metal surfaces.
A sample of the research and tools developed by our team can be found in the follow link: https://ecc-project.sandia.gov/
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.
Required skills:
A recent or soon-to-be completed 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, or Python.
Ability to create, maintain, and support high-quality software.
Strong communication skills both verbal and written.
Independent judgment and critical thinking.
Desired skills:
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.
An ideal candidate would have published their scientific software in a public repository (e.g. GitHub)
To apply for this position, please follow this link.
This position is open, and it could be filled immediately as soon a qualified candidate is found.