Research Assistant Professor
Position Type: Permanent Faculty
Department: Pharmacology - 424001
Appointment Type: Fixed Term Faculty
Vacancy ID: FAC0002582
Position Summary: We seek candidates with expertise in computational mass spectrometry and proteomics. The successful candidate will join an active group of cancer biologists, computer scientists, biochemists, and pharmacologists. The candidate is expected to integrate their expertise with faculty in the Department of Pharmacology. The candidate will also provide computational support the Michael Hooker Proteomics Center. The candidate will direct an independent research program supported by extramural funding and participate in professional and/or graduate education.
Application Deadline: 11/14/2018
Education Requirements: Candidates must have a Ph.D. in Computer Science, Mathematics, Statistics, or related fields.
Qualification and Experience: The successful candidate should have the following: Outstanding verbal and written communication skills, and the ability to collaborate effectively with other investigators and trainees. Experience with state-of-the-art liquid chromatography and mass spectrometry instruments, including their maintenance and daily operation utilizing various data acquisition strategies such as data-dependent, data-independent, and targeted methods. Hands-on experience with Orbitrap mass spectrometers is required. Experience with mass spectrometry-based proteomics data analysis, specifically with the development of pipelines for shotgun proteomics, protein-protein interactions, intact proteomics, and post-translation modifications with an emphasis on phosphorylation. Research experience in signal transduction and systems biology. Experience with MaxQuant, Perseus, OpenMS, and the TransProteomic Pipeline. Extensive and demonstrable software development skills using C/C++, Python, Java, R, Python, relational databases, and web development. Experience with machine learning and data mining tasks including classification, regression, clustering, and development of Bayesian graphical models. Excellent data visualization skills. Public speaking experience appropriate to instruct graduate and medical students as well as for service on departmental committees. Further, candidates must have multiple research publications utilizing computational approaches and instrument operation to improve the mass spectrometry-based proteomic pipeline.
Equal Opportunity Employer: The University of North Carolina at Chapel Hill is an equal opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to age, color, disability, gender, gender expression, gender identity, genetic information, national origin, race, religion, sex, sexual orientation, or status as a protected veteran.
Department Contact Name and Title: Matthew Tucci Basic Science HR Team Lead
Department Contact Telephone Number or Email: [email protected]
Special Instructions for Applicants: