Research Scientist Intern, NMR Analysis Automation Responsibilities:

• Design and execute data processing pipelines for automated analysis of NMR spectra of liquid non-aqueous battery electrolytes (1H, 7Li, 13C, 19F, 31P nuclei) with a clear, measurable speedup over manual analysis
• Implement signal processing workflows including denoising, automated peak identification and assignment, and constrained deconvolution for overlapping spectral regions in multi-component electrolyte mixtures
• Identify the optimum parameters of the pipeline that balance accuracy and throughput
• Convert NMR spectra into molecular level compositional and structural descriptors (concentrations, chemical structures) to be used for machine learning models
• Build spectral quality assessment modules that flag problematic spectra and unreliable fits

Minimum Qualifications:

• Currently pursuing a PhD in analytical chemistry, physical chemistry, chemical engineering, or a related field
• Experience with solution-state NMR spectroscopy – theory, data interpretation, and quantitative analysis
• Proficiency in Python for scientific data processing, including experience with spectral analysis or signal processing
• Experience building automated data processing pipelines or batch analysis workflow

Preferred Qualifications:

• Experience with 2D (COSY) NMR and pulse field gradient NMR experiments
• Experience designing experiments and analyzing data to validate hypotheses (e.g., DOE, statistical analysis, reproducibility studies)
• Familiarity with machine learning concepts and feature engineering for predictive models
• Background in electrochemistry or lithium-ion battery materials
• Familiarity with Bruker hardware and software, including raw data formats
• Experience with NMR of battery electrolytes, ionic liquids, or concentrated salt solutions

About Meta: