Departmental Preferred Experience, Skills, Training/Education:
REQUIREMENTS
- Ethical and self-motivated.
- Recent Ph.D. in mathematics, signal processing, image processing, computer science,
- cheminformatics, or related field.
- Solid computer programming skills in Python, R, MATLAB, Java, C++, or another programming
- languages.
- Extensive experiences in algorithm development and Big Data Analytics.
- Strong written and verbal communication skills.
- Background on metabolomics data analysis and machine learning is a plus.
Other Work/Responsibilities
- The primary research responsibilities of the successful candidates are to develop Big Data Analytics capabilities for metabolomics and exposomics and publish the results.
In particular, the successful candidates are to develop computational algorithms and software tools for:
- extracting compound information from raw liquid-chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS) exposomics and metabolomics data;
- annotating and identifying ions based on existing large-scale compound and mass spectral libraries;
- predicting possible structures or substructures of compounds using accurate mass, retention time, isotopic distribution, fragmentation spectra, and other metadata;
- integration of metabolomics and exposomics data with other -omics and meta-data for gaining a holistic understanding of the underlying biological systems.