ZipRecruiter

Log In

1

Computational Proteomics Jobs (NOW HIRING)

Bruker Corporation

Computational Biologist

$101K - $156K/yr

Overview Computational Biologist - Technical Support, Spatial Biology Bruker Spatial Biology is ... Experience analyzing high-dimensional 'omics datasets (e.g., transcriptomics, proteomics) using ...

Bruker

$101K - $156K/yr

Overview Computational Biologist - Technical Support, Spatial Biology Bruker Spatial Biology is ... Experience analyzing high-dimensional 'omics datasets (e.g., transcriptomics, proteomics) using ...

UNAVAILABLE

$101K - $156K/yr

Overview Computational Biologist - Technical Support, Spatial Biology Bruker Spatial Biology is ... Experience analyzing high-dimensional 'omics datasets (e.g., transcriptomics, proteomics) using ...

next page

Showing results 1-20

All JobsComputational Proteomics Jobs

Computational Proteomics information

See salary details

$40

$54

$74

How much do computational proteomics jobs pay per hour?

As of Jun 15, 2026, the average hourly pay for computational proteomics in the United States is $54.93, according to ZipRecruiter salary data. Most workers in this role earn between $46.88 and $73.56 per hour, depending on experience, location, and employer.

What is computational proteomics?

Computational proteomics is the application of computational methods and bioinformatics tools to analyze and interpret large-scale data generated by proteomics experiments. This field involves using algorithms, statistical models, and software to identify and quantify proteins, determine their structures, and understand their functions and interactions within biological systems. Computational proteomics is essential for managing the vast amount of data produced by techniques like mass spectrometry and for translating raw data into meaningful biological insights. Professionals in this field often work closely with experimentalists to validate findings and develop new analytical approaches.

What are the key skills and qualifications needed to thrive as a Computational Proteomics Specialist, and why are they important?

To thrive as a Computational Proteomics Specialist, you need a strong background in bioinformatics, proteomics, and data analysis, typically supported by an advanced degree in bioinformatics, computational biology, or a related field. Proficiency with mass spectrometry data analysis tools (such as MaxQuant or Proteome Discoverer), programming languages (like Python or R), and familiarity with relevant databases are essential. Strong problem-solving skills, attention to detail, and effective communication are vital soft skills for interpreting complex datasets and collaborating with multidisciplinary teams. These skills and qualifications are crucial to accurately analyze proteomic data, drive meaningful biological insights, and contribute to scientific advancements.

What are some common challenges faced by professionals working in computational proteomics, and how can they be addressed?

Professionals in computational proteomics often encounter challenges such as handling large-scale and complex datasets, integrating heterogeneous data types, and ensuring reproducibility of analyses. These can be addressed by utilizing robust bioinformatics tools, maintaining clear documentation of workflows, and collaborating closely with experimental scientists to validate computational findings. Regular participation in interdisciplinary team meetings and staying updated on the latest software advancements also help in overcoming technical and analytical hurdles.

What is the difference between Computational Proteomics vs Bioinformatics Scientist?

AspectComputational ProteomicsBioinformatics Scientist
Required CredentialsBachelor's/Master's in Bioinformatics, Biochemistry, or related fields; experience with proteomics toolsBachelor's/Master's in Bioinformatics, Computer Science, or related fields; programming skills
Work EnvironmentResearch labs, biotech companies, pharmaceutical industryResearch institutions, biotech firms, healthcare organizations
Industry UsageSpecialized in analyzing proteomics data, mass spectrometryBroader data analysis across various biological data types
Common Search/ComparisonYesYes

Computational Proteomics focuses on analyzing proteomics data, especially mass spectrometry results, requiring domain-specific knowledge. Bioinformatics Scientists have a broader scope, working with various biological data types and programming skills. While both roles share overlapping skills, Computational Proteomics is more specialized in protein data analysis within the biotech and pharmaceutical industries.

Infographic showing various Computational Proteomics job openings in the United States as of June 2026, with employment types broken down into 6% Internship, 1% As Needed, 84% Full Time, 1% Part Time, 7% Contract, and 1% Nights. Highlights an 91% Physical, 1% Hybrid, and 8% Remote job distribution, with an average salary of $114,249 per year, or $54.9 per hour.
Computational Scientist

Computational Scientist

Stowers Institute

Kansas City, MO • On-site

Full-time

Posted 13 days ago

Job description

The Stowers Institute for Medical Research seeks an accomplished computational scientist to serve as Lead of Computational Mass Spectrometry (MS) and Innovation, within our Systems Mass Spectrometry (SMS) Technology Center. The leadership role sits at the intersection of innovative technology, scientific collaboration, and the Institute's mission to advance our understanding of life's fundamental processes. The successful candidate will help drive a cutting-edge core facility at the heart of a vibrant, multidisciplinary research community, and is expected to bring a strong track record in mass spectrometry data analysis, reporting, and methodological innovation, together with exemplary communication, collaboration, and leadership skills.
Overview of the Role
Biological mass spectrometry is entering a transformative era defined by AI-enabled analysis, increasing data scale, and proteoform-level resolution. This role offers a rare opportunity to shape the analytical foundations of next-generation mass spectrometry-based multiomics (proteomics, metabolomics, lipidomics) and to define how advanced computation and AI unlock new biological and biomedical insights.The Lead of Computational MS and Innovation will be empowered to build new capabilities, pursue bold ideas, and influence the direction of biological mass spectrometry research at an institutional level.
Reporting to the Director of Systems Mass Spectrometry, the scientist will lead cutting-edge analysis of data generated by a broad portfolio of modern MS methods, including bottom-up, top-down, native, cross-linking and spatial mass spectrometry, as well as multiomics (metabolomics and lipidomics). The successful candidate will also contribute to project design, and technology development while serving as a scientific and technical resource for the Institute's investigators. The position requires deep technical expertise, collaborative spirit, and outstanding interpersonal skills, with regular interaction across more than 20 independent research programs and a spectrum of technology development facilities. They lead will also help establish standard operating protocols for results reporting and will champion cross-technology collaboration that merges new-generation mass spectrometry methods with biological discovery.
Key Responsibilities
Scientific Leadership and Strategy
  • Define and execute a long-term computational proteomics and AI innovation strategy aligned with institutional research priorities.
  • Serve as the intellectual leader for computational analysis of large-scale proteomics, native and top-down proteomics, PTM analysis, and integrative multi-omics datasets.
  • Identify emerging technologies, analytical paradigms, and AI methodologies that can transform proteomics data interpretation and biological insight.
  • Partner with computational scientists in other technology centers and PI laboratories to integrate mass spectrometry data with genomics, transcriptomics, and microscopy datasets.
  • Drive high-impact publications, presentations, and dissemination of novel computational methods.

AI-Driven Proteomics Innovation
Lead the development and deployment of machine learning and AI approaches for proteomics, including:
  • Deep learning for peptide and proteoform identification and scoring
  • AI-based spectral prediction and library-free analysis
  • Methods for both DIA and DDA acquisition strategies
  • Intelligent deconvolution, feature detection, and noise reduction
  • Automated proteoform annotation and confidence assessment
  • Explore and implement generative AI, foundation models, and representation-learning approaches for proteomics and multi-omics data.
  • Drive innovation in scalable, automated, and reproducible analysis pipelines for high-throughput proteomics.

Data Analysis and Infrastructure
  • Oversee the design, maintenance, and evolution of computational pipelines for proteomics data processing, quality control, statistical analysis, and visualization.
  • Guide the integration of proteomics data with genomics, transcriptomics, and metabolomics datasets.
  • Partner with IT and the Big Data team at Stowers to ensure robust data management, cloud/HPC utilization, and FAIR data practices.

Collaboration and Scientific Partnership
  • Work closely with experimental proteomics staff, and biological investigators to ensure computational approaches are tightly coupled to experimental design.
  • Act as a senior scientific consultant for complex studies requiring custom analysis, novel algorithms, or advanced statistical modeling.
  • Represent computational proteomics expertise in institutional initiatives, external collaborations, and consortium-based projects.

Required Qualifications
  • Masters is minimal, PhD in Chemistry, Biochemistry, Proteomics, Bioanalytical Chemistry, or a related field is strongly preferred (or equivalent experience).
  • Post-doctoral experience and/or 3 to 5 years of work experience post-graduate is strongly preferred.
  • Demonstrated hands-on experience with computational analysis of native and/or top-down mass spectrometry and proteform discovery, cross-linking mass spectrometry, and spatial mass spectrometry.
  • Experience with analysis of metabolomics datasets.
  • Experience with both DIA and DDA methods
  • Proficiency in Python, R, or similar languages, and familiarity with machine-learning frameworks (e.g., PyTorch, TensorFlow, scikit-learn).
  • Working knowledge of software platforms such as Proteome Discoverer, Skyline, Compound Discoverer, Xcalibur, or similar.
  • Experience working in a shared-resource or collaborative research environment.
  • Demonstrated ability to lead and manage scientific teams and complex projects.
  • Strong communication, organizational, and interpersonal skills.
  • Strong publication record.

Preferred Qualifications
  • Experience deploying AI/ML models in production scientific environments.
  • Familiarity with cloud computing (AWS, GCP, or Azure) and workflow managers (Nextflow, Snakemake).
  • Track record of open-source software contributions in proteomics or multi-omics.

To Apply
Submit the requested documents to careers@stowers.org or to Administration Department, Stowers Institute for Medical Research, 1000 E 50th Street, Kansas City, MO 64110.
Requested Documents:
  • Cover Letter
  • Current Resume

Apply