8 February, 2016
The Center for Proteomics is outfitted with state-of the-art nano-LC, mass spectrometers, and relevant laboratory equipment. In addition to providing a core resource to support collaborative proteomics studies within the TGen community, this facility houses a high-throughput Proteomics Biomarker Validation Unit focused on targeted proteomic technologies such as Multiple Reaction Monitoring Mass Spectrometry, antibody and nanoparticle based affinity enrichments. The Proteomics Validation Unit aligns with world-recognized experts in collaborative initiatives that engage health care professionals, policy makers, and researchers in the discovery, development, and validation of diagnostic biomarkers.
A staff scientist position with focus in mass spectrometry-based proteomics is immediately available within TGen’s Center for Proteomics.
A Staff Scientist position is immediately available within TGen’s Center for Proteomics. This is a hands-on position and the successful candidate is expecting to plan and perform appropriate sample preparation and LC-MS experiments for the identification and quantitation of peptide/proteins in samples of various complexity. He/She is expected to develop appropriate QA/QC procedures and write SOPs. The successful candidate will be expected to work effectively with an interdisciplinary team of researchers, be self-motivated, and have excellent communication skills. Candidates with experience working in regulated environments (GLP, CAP/CLIA) are desired. The successful candidate is expected to provide training and guidance to junior members of the team and lead the preparation and presentation of peer-reviewed articles, posters, and reports.
The candidate needs to be familiar with the latest generation mass spectrometers (Orbitrap, Q-TOF, QQQ, etc.) and have hands-on experience with quantitative proteomic measurements, especially absolute quantitation using isotopically labeled internal standards. The candidate will be expected to operate and troubleshoot these various instruments. Experience with other quantitative approaches (such as TMT, iTRAQ, O16:O18 labeling, label-free) in proteomic workflows and data analysis is a plus.
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