Postdoctoral researcher

The position is intended for either a postdoctoral associate with expertise in applied data science and a
strong interest in interdisciplinary research. The successful candidate will work collaboratively with
mathematicians and experimental scientists at NIST to develop mathematical and statistical algorithms
for the uncertainty quantification of seized chemical samples. These methods will support the
identification, classification, and quantification of trace chemical components, with a particular
emphasis on data generated by mass spectrometry. A such, a central objective of the project is to
develop advanced chemometric methods that improve the classification and identification of seized
drug samples, ultimately enabling more accurate prediction of spatial and temporal changes in the illicit
drug supply. The research is highly interdisciplinary and will require close collaboration with
mathematicians developing computational models and algorithms, as well as experimental scientists
responsible for collecting, processing, and interpreting the underlying measurement data.