Postdoctoral Researcher in Computational Synthesis

Job Summary

Seeking a full-time Postdoctoral Researcher in Computational Synthesis, the successful candidate will focus on training machine-learned interatomic potentials (MLIPs) and applying them to optimize the synthesis of Fe-N-C fuel cell catalysts while collaborating with a team of researchers in a dynamic research environment.

Key responsibilities

• Fine-tune foundational model MLIPs with domain-specific data and assess their accuracy
• Collaborate with researchers to study the chemistry of Fe incorporation into N-C sites for various synthetic precursors
• Develop automated workflows for analysis using AI in conjunction with NLR and partner institutions

Required qualifications

• Recent PhD graduate within the last three years
• Strong knowledge of chemistry, including molecular dynamics and reaction modeling
• Experience with MACE-based foundational models and their fine-tuning
• Proficiency in creating Python environments for training MLIPs and performing molecular dynamics
• Experience with high-throughput analysis of results