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The primary research responsibilities of the successful candidates are to develop data mining and big data analytics capabilities for metabolomics, exposomics, and -omics data integration and publish the results. In particular, the successful candidates are to develop computational algorithms, workflows, software tools, and cloud resources for: (1) extracting compound information from raw liquid-chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS) exposomics and metabolomics data; (2) annotating and identifying ions based on existing large-scale compound and mass spectral libraries; (3) integration of metabolomics and exposomics data with other -omics and meta-data for gaining a holistic understanding of the underlying biological systems, and (4) data mining large-scale databases for extracting biological knowledge.

In addition to carrying out research, the successful candidates will also share student mentoring with Dr. Du.

As an EOE/AA employer and an ADVANCE Institution that strives to create an academic climate in which the dignity of all individuals is respected and maintained, the University of North Carolina at Charlotte encourages applications from all underrepresented groups. Applicants subject to criminal background check.

Ph.D. (obtained in 2017 or later) in mathematics, statistics, chemistry, or bioinformatics.

· Ethical and self-motivated.

· Solid computer programming skills in Python, R, MATLAB, Java, or other programming languages.

· Extensive experiences in algorithm development and statistical analysis of real data.

· Strong written and verbal communication skills.

· Experiences in metabolomics data analysis and machine learning are a big plus.

· Passionate for research and problem-solving.