Postdoctoral Appointee-Developing an Exascale MuPhFASa (Multi Phase Flow Adaptive Simulator)
About The Position
The Argonne Leadership Computing Facility (ALCF) and the Computational Science (CPS) Division are seeking a postdoctoral appointee. The ALCF's mission is to accelerate scientific discoveries and engineering breakthroughs by providing world-leading computing facilities. The CPS Division focuses on solving challenging scientific problems through advanced modeling and simulation on capable computers, building lab-wide simulation application capabilities, and integrating with mathematics, computer science, domain science, and advanced computing architectures. The successful candidate will develop computational fluid dynamic (CFD) tools to make exascale computing accessible to a broader user base. This involves developing a massively parallel solver for the Aurora supercomputer using AMReX and the lattice Boltzmann method (LBM), and creating physics-based adaptation algorithms for smarter, more efficient simulations. The role requires a strong CFD background and LBM expertise to develop methodologies applicable to diverse problems such as bubbly flow, emulsions, sedimentation, wetting, gas-mixing, and red-blood cell flow. The ideal candidate is intellectually curious, enthusiastic about computational research, intrinsically driven, goal-oriented, and collaborative. Working with the CPS division, the postdoc will leverage AMReX and LBM to develop an integrated framework for advanced workloads, including in-situ visualization and potential machine learning integration, which will inform future ALCF platform procurement decisions.
Requirements
- Recent or soon-to-be-completed Ph.D. (typically completed in the last 5 years) in mechanical/aerospace/chemical engineering, applied mathematics or a related discipline
- Experience in numerical methods and CFD development using mesh-based scientific codes
- Expertise in the lattice Boltzmann method (LBM) as evidenced by their publications
- High performance computing (HPC) experience in code development with parallel programming techniques using the message passing interface (MPI) library
- Proficiency in writing code with C, C++ and/or Python
- Ability to demonstrate strong written and oral communication skills
- Ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork
Nice To Haves
- Experience with two-phase/multi-phase flows as evidenced by their publications
- Experience programming GPUs with CUDA, SYCL, HIP or OpenMP
- Experience using and developing code with AMReX
- Experience in performance engineering to improve code scalability and reduce time-to-solution
Responsibilities
- Develop computational fluid dynamic (CFD) tools that make exascale computing accessible to a broader set of users
- Develop a massively parallel solver, capable of running simulations on the Aurora supercomputer, using AMReX and the lattice Boltzmann method (LBM)
- Develop flow/geometry-aware refinement strategies that go beyond traditional error estimators, creating physics-based adaptation algorithms that intelligently predict where refinement will be most beneficial for smarter, more efficient simulations
- Develop methodologies broad enough to tackle a diverse set of problems, appealing to a wide range of computational science users
- Leverage AMReX and the LBM to develop an integrated framework to explore advanced workloads including simulations with in-situ visualization and, possibly, machine learning integration
Benefits
- Comprehensive benefits
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Entry Level
Education Level
Ph.D. or professional degree
Number of Employees
1,001-5,000 employees
