Research Scientist

Employment Type: Permanent Staff (EHRA NF)

Vacancy ID: NF0010198

Salary Range: Dependent on Qualifications/Experience

Position Summary/Description:

The Research Scientist will join the Metabolomics and Proteomics ( MAP ) Core at the University of North Carolina at Chapel Hill, a collaborative shared research facility that supports investigators across UNC and external partners through advanced metabolomics, proteomics, mass spectrometry, and data analysis services. This position offers an exciting opportunity to contribute to cutting-edge translational and biomedical research while working with multidisciplinary teams on a wide range of sponsored research projects.

The Research Scientist will provide scientific expertise in metabolomics, mass spectrometry, analytical method development, bioinformatics, and multi-omics data integration. Responsibilities include designing and conducting complex research studies; developing and implementing specialized analytical and computational approaches; analyzing, integrating, and interpreting metabolomics and multi-omics datasets; and communicating findings through publications, presentations, and collaborative research activities.

Working closely with faculty investigators, MAP Core leadership, and research teams, the Research Scientist will serve as a key scientific resource supporting multiple research programs. The position works with a high degree of independence, exercising independent scientific judgment in experimental design, analytical methods, and data interpretation. The successful candidate will contribute to the advancement of metabolomics and multi-omics technologies and applications and help further UNC’s research mission through innovation, collaboration, and scholarly contributions.

Education and Experience:

Ph.D. in Analytical Chemistry, Bioanalytical Chemistry, Biochemistry, Pharmacology, or a closely related scientific discipline.

Two to four years of postdoctoral, research scientist, or equivalent advanced research experience in metabolomics, mass spectrometry, analytical chemistry, computational biology, or translational biomedical research.

Experience developing and validating targeted quantitative LC-MS/MS assays, including use of stable isotope-labeled internal standards and calibration curves.

Experience in computational data analysis and bioinformatics, including proficiency in R, Python, or a comparable programming language for data processing, statistical analysis, and visualization.

Experience developing reproducible computational workflows, including version control and high-performance computing environments.

Demonstrated experience integrating multi-omics datasets (e.g., metabolomics, lipidomics, proteomics, transcriptomics) to address biological questions, including use of data integration methods and tools and multivariate statistical or machine learning approaches for high-dimensional biological data.

Experience in systems biology, such as pathway and network analysis, metabolic modeling, or metabolic flux analysis.

Experience supporting multiple investigators and translational, clinical, or biomedical research programs, such as in a core facility.

Strong record of peer-reviewed publications, including first-author publications, in metabolomics, lipidomics, mass spectrometry, bioinformatics, analytical chemistry, or related fields, and of presenting scientific findings at regional, national, or international scientific meetings.

Experience contributing to successful grant applications.

Demonstrated experience mentoring students, trainees, postdoctoral scholars, or research staff.

Essential Skills:

Demonstrated experience conducting independent scientific research, including designing and executing complex research studies and experimental workflows.

Demonstrated scholarly productivity through peer-reviewed scientific publications.

Extensive experience conducting LC-MS/MS-based metabolomics and/or lipidomics research on high-resolution mass spectrometry platforms, including acquiring, analyzing, and interpreting complex datasets.

Experience preparing biological samples, such as tissues, cells, plasma, or serum, for mass spectrometry analysis

Experience with metabolomics data processing and analysis software (e.g., Compound Discoverer, LipidSearch, Skyline, MetaboAnalyst).

Experience collaborating on multidisciplinary research projects and sponsored research activities.

AA/EEO Statement:

The University is an equal opportunity employer and welcomes all to apply without regard to age, color, gender, gender expression, gender identity, genetic information, national origin, race, religion, sex, or sexual orientation. We encourage all qualified applicants to apply, including protected veterans and individuals with disabilities.