Researcher 5 in Quantitative Proteomics

Researcher 5 in Quantitative Proteomics ztflaten  2021-01-19

Job description:

This is an exciting growth opportunity that focuses on large-scale quantitative proteomics applications in the Li Lab at the University of Minnesota’s Medical School and the Graduate Neuroscience Program. Our expertise and research has been focused on applying cutting edge quantitative proteomics to identify novel mechanisms and biomarkers for precision and personalized treatment of neurodegenerative diseases. The individual will be scientifically responsible for aspects of research planning, method development, sample preparation, data acquisition and biostatistics and bioinformatics. Responsibilities also include effectively communicating project progress, teaching and mentoring lab staff and graduate student, large-scale data analyses using biostatistics and bioinformatics, preparing presentations, and participating in grant writing and scientific publications in high impact journals.


Conduct investigations or experiments in an assigned area to aid in the solution of a research problem.
Set up and operate equipment used in collecting research data.
Calculate and analyze data.
Select and review literature relating to the assigned area.
Actively participate in research efforts by exploring new possible approaches to problems and discuss possible approaches to problems with supervisor.
Write routine summary reports on results of work and confer with supervisor on interpretation of results and avenues of investigation.
Write manuscripts as author and/or co-author for publication

Required Qualifications:

Masters degree (chemistry, biochemistry or related discipline) with at least one year of experience
Significant background in proteomics
A clear record of publications
Proficiency in bioinformatics approaches including protein quantification, statistical analyses, and pathway analysis
Outstanding communication skills

Preferred Qualifications:

PhD (chemistry, biochemistry or related discipline)
Programming experience
Direct experience with data-independent acquisition

Lab Website:

Apply here: