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Computer Science Proteomics Jobs (NOW HIRING)

Merck & Co.

... proteomics data with other omics data from patient cohorts and preclinical models to identify ... PhD in Data Science, Computational Biology, Computer Science, Neuroscience, Bioinformatics ...

UAB

COMPUTATIONAL SCIENTIST ASSOCIATE

Tampa, FL · On-site

Develop computational pipelines for analysis of genomic, transcriptomic, proteomic, and other high ... Bachelor's degree in computer science, engineering, medical physics, biomedical engineering, data ...

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Computer Science Proteomics information

How does a Computer Science Proteomics professional typically collaborate with biologists and lab researchers on data analysis projects?

Computer Science Proteomics professionals often work closely with biologists and lab researchers to interpret complex proteomic data. They translate experimental requirements into computational workflows, assist in developing algorithms for protein identification and quantification, and present data results in accessible formats. Effective communication and interdisciplinary teamwork are essential, as these professionals bridge the gap between raw data and biological insight. Regular meetings, collaborative troubleshooting, and joint publications are common aspects of this collaboration.

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

To thrive as a Computer Science Proteomics Specialist, you need a solid background in computer science, bioinformatics, and proteomics, often supported by advanced degrees in related fields. Familiarity with mass spectrometry data analysis tools, programming languages like Python or R, and bioinformatics software is typically required. Strong analytical thinking, problem-solving, and communication skills help you interpret complex data and collaborate with interdisciplinary teams. Mastery of these skills ensures accurate protein analysis and drives meaningful biological discoveries in research and applied settings.

What is computer science proteomics?

Computer science proteomics is an interdisciplinary field that combines computational methods with proteomics, the large-scale study of proteins, to analyze and interpret complex biological data. Professionals in this area develop algorithms, software, and databases to process data from mass spectrometry and other experiments, enabling researchers to identify, quantify, and understand proteins and their functions. This field is crucial for advancing our knowledge in biology, medicine, and biotechnology, as it helps to uncover protein interactions, modifications, and their roles in diseases.

What is the difference between Computer Science Proteomics vs Bioinformatics?

AspectComputer Science ProteomicsBioinformatics
Required CredentialsBachelor's or Master's in Computer Science, Bioinformatics, or related fieldsBachelor's or Master's in Bioinformatics, Biology, or related fields
Work EnvironmentResearch labs, biotech companies, academic institutionsResearch labs, healthcare, biotech, academia
Industry UsageAnalyzing proteomics data using computational methodsAnalyzing biological data, including genomics and proteomics
Search & Comparison IntentFocus on computational analysis of proteomics dataBroader biological data analysis including proteomics

Computer Science Proteomics primarily involves developing computational tools to analyze proteomics data, while Bioinformatics encompasses a broader range of biological data analysis, including genomics and proteomics. Both roles require similar educational backgrounds but differ in focus and application areas.

Infographic showing various Computer Science Proteomics job openings in the United States as of May 2026, with employment types broken down into 20% As Needed, 20% Temporary, 40% Contract, and 20% Nights. Highlights an 91% Physical, 1% Hybrid, and 8% Remote job distribution.
Computational Scientist

Computational Scientist

Stowers Institute

Kansas City, MO • On-site

Full-time

Posted 5 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