Research Assistant Professor in Proteomics, Metabolomics, and Lipidomics

Research Assistant Professor in Proteomics, Metabolomics, and Lipidomics

Join to apply for the Research Assistant Professor in Proteomics, Metabolomics, and Lipidomics role at The University of Texas at El Paso

The Department of Biological Sciences invites applications for a non‑tenure‑track faculty position as a Research Assistant Professor in the areas of Proteomics, Metabolomics, and Lipidomics, beginning Spring 2026. The appointment will be for 12 months, renewable for up to 3 years; renewal beyond that will depend on the successful candidate’s ability to secure extramural funding. We seek an innovative, highly collaborative scientist with a strong background in Biochemistry, Chemistry, and/or Molecular Biology.

Candidates with expertise in generating, analyzing, and curating large‑scale omics datasets, including proteomic, lipidomic, metabolomic, glycomic, and/or glycopeptidomic data, are especially encouraged to apply.

Location: El Paso, TX

The successful candidate will oversee and maintain state‑of‑the‑art core instrumentation in the Biomolecule Analysis and Omics Unit within the Department of Biological Sciences, participate in collaborative research programs across the Colleges of Science, Health Sciences, Engineering, and the School of Pharmacy, secure extramural funding independently or collaboratively, publish in high‑impact peer‑reviewed journals, and contribute to the training of undergraduate and graduate students, postdoctoral fellows, and technical staff.

The candidate will also conduct workshops and training sessions in proteomics, metabolomics, lipidomics, glycomics, glycopeptidomics, and related omics data analysis.

Candidates must hold a Ph.D. (or equivalent) in a relevant field and have a minimum of two years of postdoctoral experience. Applicants must demonstrate a strong record of research productivity and a clear potential to secure external funding. Competitive applicants will provide documented evidence of the following.

• Grant writing & extramural funding:
  Experience writing or contributing to instrumentation grants, research grants, or collaborative proposals.
• Demonstrated success in collaborative research and peer‑reviewed publications.
• Experience with core facility management:
  • Oversight of day‑to‑day core operations, user training, scheduling, and service coordination.
  • Development of Standard Operating Procedures (SOPs) and quality‑control workflows.
  • Maintenance and troubleshooting of core instrumentation.
• Instrument method development & optimization:
  Proven ability to develop, optimize, and validate LC‑MS/MS methods for complex sample types.
• Expertise in extracting proteins, metabolites, and lipids and performing nano‑ and micro‑flow LC‑HR‑MS/MS for comprehensive multi‑omics analysis.
• Proficiency in Python and R (essential) for data analysis, modeling, and visualization.
• Ability to work effectively within diverse, multidisciplinary teams of faculty, staff, and students from varied backgrounds.
• Commitment to involving students in research, mentoring, and publication opportunities.
• Compliance, safety, and regulatory knowledge:
  Knowledge of laboratory safety, chemical hygiene, and data integrity standards (QA/QC practices).

• Familiarity with data processing and interpretation using widely used, field‑standard software tools:
  • Proteomics:
    Proteome Discoverer, Max Quant + Perseus, Spectronaut (DIA), Frag Pipe/ MSFragger, and Scaffold
  • Lipidomics:
    Lipid Search, MS‑DIAL, Lipid Match, and Skyline
  • Metabolomics:
    Compound Discoverer, XCMS, MZmine 3, MS‑DIAL, and Trace Finder (targeted)
  • Glycoproteomics/Glycomics:
    Byonic, pGlyco3, Sim Glycan, Glyco Workbench / Glycan Builder
  • Small‑Molecule Quantification:
    Skyline, Trace Finder, Multi Quant, Quan Lynx
  • Multi‑Omics Integration:
    Metabo Analyst, Network Analyst/Omics Net, and Cytoscape
• Experience in analyzing genomics and transcriptomics data sets.
• Application of advanced statistical modeling and bioinformatics tools for comprehensive multi‑omics data integration and interpretation.
• Successful teaching experience at the university/community college level.
• Strong communication &…