Dr. Vasilis Vasiliou, Chair of the Environmental Health Sciences Department at the Yale School of Public Health (New Haven, CT, USA), is seeking a bioinformatician for the role of Postdoctoral Research Associate.  Experience in “big data� analysis, specifically in the fields of mass spectrometry-based metabolomics, exposomics, and/or tissue imaging mass spectrometry, is preferred.

Dr. Vasiliou’s research focuses on investigating the etiologies and molecular mechanisms of environmentally-induced human disease, such as liver disease, obesity & diabetes, cancer, and neurodegenerative diseases. More specifically, research in his lab focuses on the means by which the exposome (total exposures throughout life), metabolism (specifically aldehyde dehydrogenases and cytochrome P-450s) and antioxidants (glutathione and catalase) contribute to human health and disease. Dr. Vasiliou’s laboratory utilizes state-of-the-art integrated system approaches that include metabolomics, lipidomics, redox proteomics, exposomics, tissue imaging mass spectrometry, machine-learning, as well as human cohorts and genetically-engineered mouse models in order to elucidate mechanisms, and to discover biomarkers and novel interventions for human disease. His laboratory is fully equipped with 4 state-of-the-art mass spectrometers, a UHPLC-QTOF MS (Waters), a UHPLC-QqQ MS with an ESI source (Waters), a QTOF with a MALDI and DESI source (Waters) and a GC-MS (Agilent).

The primary research field of a successful candidate includes developing “Big Data� analytics capabilities for metabolomics, exposomics and tissue imaging mass spectrometry in collaboration with Dr. Vasiliou’s group, as well as the group’s collaborator from Imperial College London.  Specifically, a successful candidate should be capable of developing computational algorithms and software tools in collaboration with the Vasiliou lab, for:

(1) Extracting compound information from raw liquid-chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS) metabolomics, exposomics and tissue imaging mass spectrometry data.

(2) Annotating and identifying ions based-on existing large-scale compound and mass spectral libraries.

(3) Integrating metabolomics and exposomics data with other -omics/meta-data for biological applications.

(4) Developing algorithms and software tools for tissue imaging mass spectrometry data interrogation.

This position will be funded for two years, with the potential for extension. The candidate will be expected to apply for additional external postdoctoral funding (e.g., F32 or other foundations), publish original research and assist in writing other grant applications.