Postdoctoral Researcher – Computational Synthesis of PGM-free Fuel Cell Catalysts
About The Position
The Advance Computing Solutions group in the NLR Computational Science Center has an opening for a post doctoral researcher in computational synthesis, with a particular emphasize on machine-learned interatomic potentials (MLIPs). The researchers will train MLIPs, assess their accuracy and apply them to studying the relevant reaction energetics for synthesis of Fe-N-C fuel cell catalysts using automated workflows. In conjunction with a team of staff scientists, different synthetic precursors will be identified for subsequent synthesis. We are looking for a dynamic, motivated researcher with a strong technical background and an interest in the mission of NLR. The successful candidate will collaborate with NLR staff and researchers to train and deploy MLIPs for the optimization of Fe-N-C catalyst synthesis.
Requirements
- Must be a recent PhD graduate within the last three years.
- Must meet educational requirements prior to employment start date.
- Excellent written and verbal communication skills.
- Excellent knowledge of chemistry, including molecular dynamics and reaction modeling
- Experience with the MACE-based foundational models and their fine-tuning
- Experience with creating python environments for training MLIPs, performing MLIP-based molecular dynamics and nudged-elastic band calculations, and performing analysis of results with high throughput
Nice To Haves
- Knowledge of workflow automation, including the use of AI for automated analysis of data.
- Experienced running density functional theory (DFT) software packages such as JDFTx for VASP.
Responsibilities
- Fine-tuning of foundational model MLIPs with domain-specific data and assessment of their accuracy
- Collaboration with NLR researchers to use the trained MLIPs to study the chemistry of Fe incorporation into N-C sites for different synthetic precusors
- Developing automated workflows in conjunction with NLR and collaborating institutions, including automated analysis using AI
- Processing and visualizing results from simulations provide chemical insight and intuition into important chemical reactions.
- Authoring, presenting and assisting in the preparation of technical papers, reports and conference proceedings on topics related to MLIP studies of the synthesis of Fe-N-C fuel cell catalysts.
Benefits
- medical, dental, and vision insurance
- short-term disability insurance
- pension benefits
- 403(b) Employee Savings Plan with employer match
- life and accidental death and dismemberment (AD&D) insurance
- personal time off (PTO) and sick leave
- paid holidays
- performance-, merit-, and achievement- based awards that include a monetary component
- relocation expense reimbursement
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
Education Level
Ph.D. or professional degree
