Post Doctoral Fellowship - AI/ML Model Developer

Project Overview:

This project aims to develop AI/ML models to calibrate multi-physics models in DOE-based codes such as PFLOTRAN. PFLOTRAN is an open-source, state-of-the-art, massively parallel subsurface flow and reactive transport code. PFLOTRAN solves a system of generally nonlinear partial differential equations describing multiphase, multicomponent, and multiscale reactive flow and transport in porous materials. The code is designed to run on massively parallel computing architectures, workstations, and laptops. We have developed an initial workflow to integrate PFLOTRAN models with field/experimental datasets related to reactive transport and hydro-bio-geophysics. The participant will be able to work with PFLOTRAN developers and AI/ML researchers to enhance the AI/ML workflow on high-performance computing systems. These trained AI/ML models and calibrated PFLOTRAN process models have direct relevance to DOE-EM mission areas with applications such as remediation and river-water intrusion.

Preferred Skills:

• Data science
• basic Python programming
• basic experience with Linux or shell scripting.

Must be a US Citizen or able to obtain DOE Clearance