Postdoctoral scholar in multivariate analysis of FT-IR spectra of atmospheric aerosols
A postdoctoral position is available in the area of multivariate analysis of FT-IR spectra of atmospheric particulate matter (PM). The FT-IR Laboratory in the Air Quality Research Center (AQRC) at UC Davis uses mid-infrared spectra and multivariate calibration models to predict the composition of filter-based PM samples in U.S. and international PM networks. Particulate matter is composed of thousands of organic compounds, elemental carbon, inorganic ions and elements that vary in time and space due to varying atmospheric processes and a wide range of anthropogenic and natural sources of air pollution such as transportation, industry, wood-burning stoves, wildfires, and dust. The postdoctoral scholar will use multivariate calibrations, primarily partial least squares regression to develop, evaluate, and improve calibrations of organic functional groups (Boris et al., amt-2019-144, 2019; Ruthenburg et al., j.atmosenv.2013.12.034, 2014), organic and elemental carbon (Weakley et al., 02786826.2018.1439571, 2018; Burki et al., amt-13-1517-2020, 2020), ions and elements (in preparation), using both ambient samples and laboratory standards as reference values. Statistical methods and models, such as principal component analysis, Gaussian mixture models, and cluster analysis tools, are further applied to assess compositional and source similarity. In addition, the postdoctoral scholar will work to improve quality control procedures for predicting these quantities in an existing monitoring network. Data will be available from the IMPROVE network, (http://vista.cira.colostate.edu/Improve/, ~20,000 samples from National Parks and Wilderness Areas per year), CSN (~13,000 samples from US urban sites each year), SPARTAN (www.spartan-network.org, ~600 samples from highly polluted international sites per year) as well as from research campaigns.
The initial appointment is for one year and may be extended up to an additional four years contingent upon funding and mutual agreement. The position includes health insurance and other benefits.
The candidate must have a PhD in Atmospheric Science, Chemistry, Chemical or Environmental Engineering or a related field. Strong Matlab and/or R skills are required along with a strong background in numerical methods, statistical learning approaches, and/or familiarity with chemometrics. Research experience in chemometrics, machine learning, FT-IR spectroscopy, and/or atmospheric aerosol organic chemistry are desirable. Interested individuals should send a single pdf file containing a cover letter, CV, graduate transcripts, date of availability, contact information of three references, and up to three published papers to Dr. Ann M. Dillner (amdillner at ucdavis dot edu). More information on Dr. Dillner’s laboratory, the FT-IR Laboratory in the Air Quality Research Center (AQRC) at UC Davis is available at https://aqrc.ucdavis.edu/people/ann-dillner. Applications will be reviewed beginning November 2, 2020 but will be accepted until the position is filled.
The University of California, Davis, is an affirmative action/equal opportunity employer with a strong institutional commitment to the development of a climate that supports equality of opportunity and respect for differences.
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