A position is available for a Research Associate at the UNC Proteomics Core Facility (proteomics.unc.edu). As a University-operated recharge core, the Proteomics Core Facility offers mass-spectrometry based proteomics services to internal and external researchers across the United States. Current instrumentation at the UNC Proteomics Core includes five mass spectrometers: Thermo Exploris 480, Orbitrap Fusion Lumos, QExactive HF, QExactive HF Biopharma and Sciex 5800 MALDI-TOF/TOF. In addition to the mass spectrometers, there are three Thermo Easy nLC 1200s, an Ultimate3000, and a 908 Devices ZipChip capillary electrophoresis device for up-front separation, and an Agilent 1260 Infinity II HPLC for offline peptide fractionation. Several software packages are available: Proteome Discoverer 2.5, Scaffold v4, Byos, Spectronaut Biognosys, MaxQuant, Skyline, Ingenuity Pathway Analysis.
The Research Associate will work with other Proteomics Core members and collaborators to design experiments and manage projects. Project types can include: post-translational site mapping, protein-protein interaction analysis, deep quantitative proteomics and phosphoproteomics. The Research Associate will assist in various aspects of these projects including sample preparation, LC-MS/MS analysis and/or data analysis and interpretation.
Education and Experience:
The successful candidate will work on multiple projects at the same time; therefore, strong multitasking and time management skills, as well as the ability to work independently and efficiently is required. The successful candidate will work closely with the other Proteomics Core team members, as well as collaborators from multiple labs; therefore, strong communication and interpersonal skills are required.
The applicant will have two or more years of post-bachelor's degree experience in proteomics or another mass spectrometry-based field. Experience with sample preparation, and/or analyzing complex -omics datasets is required. Experience with different types of proteomics software (for example, Proteome Discoverer, MaxQuant, Spectronaut) is preferred. Preference will be given to candidates with statistical (using R, Python) and bioinformatics expertise. The applicant will have a working knowledge or experience with cell biology, common biochemical and proteomics sample preparation techniques. The applicant will have working knowledge or experience with LC-MS instruments.
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