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Research Faculty Bioinformatics and Proteomics Software Development; NHMFL

Job in Tallahassee, Franklin County, Florida, 32318, USA
Listing for: National High Magnetic Field Laboratory
Full Time position
Listed on 2026-09-23
Job specializations:
  • Research/Development
    Research Scientist, Data Scientist, Biomedical Science, Biotech Research
Salary/Wage Range or Industry Benchmark: 90000 - 130000 USD Yearly USD 90000.00 130000.00 YEAR
Job Description & How to Apply Below
Position: Research Faculty (Open Rank) - Bioinformatics and Proteomics Software Development (NHMFL)
Location: Tallahassee

Department

Ion Cyclotron Resonance (ICR) Program, National High Magnetic Field Laboratory (NHMFL). The NHMFL is operated for the National Science Foundation by a collaboration of institutions comprising Florida State University, the University of Florida, and Los Alamos National Laboratory and houses the world’s premier ICR laboratory, with state-of-the-art FT-ICR mass spectrometers that operate at 21 T, 14.5 T, 9.4 T, and 9.4 T, for research in chemistry, materials science, engineering, geochemistry, biochemistry, and biology.

Current areas include natural organic matter, emerging environmental contaminants, biofuels, top-down proteomics, lipidomics, metabolomics, and mass spectrometry imaging.

Responsibilities

The ICR Program seeks a research faculty member with expertise in bioinformatics, computational mass spectrometry, and scientific software development. The successful candidate will collaborate with researchers in the ICR Program to develop, implement, and validate novel algorithms for the analysis of high-resolution mass spectrometry data, with particular emphasis on top-down proteomics, de novo sequencing, proteoform characterization, and related applications in metabolomics and lipidomics.

The candidate will contribute to the design of software tools and computational workflows for processing data generated by state-of-the‑art FT-ICR and Orbitrap mass spectrometers.

The candidate is expected to collaborate with NHMFL staff, graduate students, postdoctoral fellows, and external users; publish manuscripts; present at scientific conferences; and contribute to applications for external research funding. Additional responsibilities include maintaining software resources, supporting users with computational aspects of their projects, and helping to establish robust and reproducible data analysis pipelines for the ICR user community.

Qualifications

Candidates are expected to have a Ph.D. in Bioinformatics, Computer Science, Computational Biology, Analytical Chemistry, Data Science, or a closely related STEM field, along with experience conducting interdisciplinary research in a collaborative environment. For the Research Faculty I level, 2-5 years of additional experience in these areas is required. For the rank of Research Faculty II or III, 6-9 or 10+ years, respectively, of additional experience is required.

The successful candidate must have demonstrated expertise in software development and scientific programming in Python, including the ability to independently design, implement, test, and maintain research software, scientific algorithms, and computational workflows. Candidates should have a record of scholarly achievement through peer‑reviewed publications, software development, or other research accomplishments and experience analyzing large, complex biological datasets. Applicants must demonstrate experience developing computational tools through peer‑reviewed software publications, publicly available software packages, Git Hub repositories, or equivalent evidence of software development.

Preferred Qualifications

Desired qualifications include experience with mass spectrometry‑based proteomics, metabolomics, lipidomics, or related omics disciplines; development of algorithms and software for scientific data analysis; database searching and identification workflows for proteins, peptides, metabolites, or other biomolecules; and quantitative analysis of biological datasets. Experience applying artificial intelligence, machine learning, graph‑based methods, pattern recognition, or statistical modeling to biological data is highly desirable. Additional experience with de novo sequencing, computational mass spectrometry, high‑performance computing, and open‑source software…

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