Opportunity Description:

The Skinnider Lab of the Ludwig Princeton Branch at Princeton University aims to recruit one to two postdoctoral associates or more senior research positions to work on projects related to computational analysis of and machine-learning approaches to mass spectrometry-based metabolomics and/or proteomics data. Successful candidates will develop and apply computational approaches for mass spectrometry data, with artificial intelligence/machine learning (AI/ML) being a major focus. They will have an opportunity to lead and contribute to a range of exciting projects: for example, developing machine-learning approaches for the identification of known and unknown metabolites in MS/MS data; meta-analysis of mass spectrometry-based metabolomics from human disease; novel approaches to proteomic data analysis; or curation and development of new data resources. Individuals should have or be expected to have a PhD with appropriate research experience in computational biology, chemistry, biochemistry, computer science, biological engineering, or a related field.