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Computational Proteomics Jobs (NOW HIRING)

Develop computational pipelines for analysis of genomic, transcriptomic, proteomic, and other high-throughput biological datasets. * Support analysis of RNA sequencing, whole exome sequencing ...

Computational Biologist

Chicago, IL · On-site

$130K - $163K/yr

Integrate proteomics, metabolomics, and related datasets, and explore machine learning or transfer ... PhD in bioinformatics, computer science, statistics, computational biology, biomedical engineering ...

Computational Biologist

Chicago, IL · On-site

$130K - $163K/yr

Integrate proteomics, metabolomics, and related datasets, and explore machine learning or transfer ... PhD in bioinformatics, computer science, statistics, computational biology, biomedical engineering ...

DIRECTOR, COMPUTATIONAL BIOLOGY SUMMARY: We are seeking an exceptional computational biologist to ... In this role, you will drive the use of high-throughput, transcriptomics, epigenomics, proteomics ...

URUS is seeking a Computational Biologist to join our Innovation group as part of the team focused ... Knowledge of specific tools, databases, and analysis methods for genomic/proteomic data.

URUS is seeking a Computational Biologist to join our Innovation group as part of the team focused ... Knowledge of specific tools, databases, and analysis methods for genomic/proteomic data.

URUS is seeking a Computational Biologist to join our Innovation group as part of the team focused ... Knowledge of specific tools, databases, and analysis methods for genomic/proteomic data.

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Computational Proteomics information

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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 - Hematology & Medical Oncology

Computational Scientist - Hematology & Medical Oncology

Mount Sinai Hospital

Manhattan, NY • On-site

Full-time

Posted 14 days ago


Mount Sinai rating

7.8

Company rating: 7.8 out of 10

Based on 280 frontline employees who took The Breakroom Quiz

130th of 872 rated healthcare providers


Job description

Job Description
The Computational Scientist I will develop and maintain scalable, modular bioinformatics pipelines for antigen discovery and prioritization, and integrative analysis of genomic (e.g., WES/WGS), transcriptomic (e.g., RNA-seq), and proteomic (e.g., mass spectrometry) data. The role focuses on building reproducible, end-to-end computational workflows for processing, analyzing, and interpreting high-throughput multi-omic datasets in a cancer immunogenomics setting.
The role will contribute to development of computational platforms supporting translational cancer immunotherapy research, with applications in clinical trial settings for the design of personalized and shared (off-the-shelf) vaccine strategies.
The candidate will join a multidisciplinary team with extensive experience in computational immunogenomics and translational cancer research. The group has developed and applied the OpenVax platform in support of multiple clinical trial efforts focused on cancer vaccine strategies. Working closely with this team, the Computational Scientist will contribute to extending existing capabilities, introducing new computational functionality, and advancing the development of next-generation analytical workflows and platforms.
The position involves working with next-generation sequencing and proteomic datasets to perform data processing, quality control, and integrative analysis. The individual will design, implement, and maintain modular pipeline components across data processing, analysis, and reporting layers, ensuring scalability, reproducibility, and portability across computational environments.
Responsibilities
  • Develop, implement, and maintain scalable bioinformatics pipelines for genomic, transcriptomic, and proteomic data analysis
  • Design modular components for end-to-end workflows, including data ingestion, preprocessing, analysis, and reporting
  • Integrate multi-omic datasets to support antigen discovery and prioritization
  • Perform data processing, quality control, and validation of high-throughput sequencing and proteomic datasets
  • Benchmark, optimize, and validate computational methods and workflows
  • Package and deploy pipelines in reproducible environments (e.g., Docker, Singularity) and support execution on HPC systems
  • Manage and analyze large-scale datasets in HPC environments
  • Generate structured outputs, visualizations, and reports for downstream biological interpretation
  • Collaborate with computational, experimental, and clinical teams to translate analytical results into translational insights
  • Contribute to scientific reports, presentations, and manuscripts
  • Stay current with emerging computational methods in genomics and immunogenomics
  • Perform other related duties as assigned

Qualifications
  • Masters degree or equivalent in a domain science; Ph.D in a scientific domain preferred.
  • 3 years, preferably in a scientific/academic computing environment or equivalent experience.
  • Preferred qualifications:
    • Strong proficiency in Python for scientific computing and pipeline development, with an emphasis on software engineering best practices (e.g., code structure, version control, testing, and documentation)
    • Experience developing, maintaining, or extending bioinformatics pipelines or computational workflows
    • Experience working with next-generation sequencing (NGS) data (e.g., RNA-seq, WES/WGS), including data processing and quality control
    • Familiarity with genomic and transcriptomic data analysis concepts
    • Experience working with large-scale datasets in high-performance computing (HPC) or cloud-based environments
    • Familiarity with containerization and reproducible workflows (e.g., Docker, Singularity) is preferred
    • Experience with workflow management systems (e.g., Nextflow, Snakemake) is a plus
    • Exposure to proteomic data (e.g., mass spectrometry) and/or multi-omic data integration is a plus
    • Experience with data visualization and generation of structured outputs for scientific interpretation is a plus
    • Familiarity with cancer genomics or immunogenomics
    • Ability to work independently on defined tasks and collaboratively within a multidisciplinary team
    • Strong communication skills, with the ability to clearly present computational results to scientific collaborators
    • Strong organizational skills and attention to detail

About Us
Strength through Unity and Inclusion
The Mount Sinai Health System is committed to fostering an environment where everyone can contribute to excellence. We share a common dedication to delivering outstanding patient care. When you join us, you become part of Mount Sinai's unparalleled legacy of achievement, education, and innovation as we work together to transform healthcare. We encourage all team members to actively participate in creating a culture that ensures fair access to opportunities, promotes inclusive practices, and supports the success of every individual.
At Mount Sinai, our leaders are committed to fostering a workplace where all employees feel valued, respected, and empowered to grow. We strive to create an environment where collaboration, fairness, and continuous learning drive positive change, improving the well-being of our staff, patients, and organization. Our leaders are expected to challenge outdated practices, promote a culture of respect, and work toward meaningful improvements that enhance patient care and workplace experiences. We are dedicated to building a supportive and welcoming environment where everyone has the opportunity to thrive and advance professionally. Explore this opportunity and be part of the next chapter in our history.
About the Mount Sinai Health System:
Mount Sinai Health System is one of the largest academic medical systems in the New York metro area, with more than 48,000 employees working across eight hospitals, more than 400 outpatient practices, more than 300 labs, a school of nursing, and a leading school of medicine and graduate education. Mount Sinai advances health for all people, everywhere, by taking on the most complex health care challenges of our time - discovering and applying new scientific learning and knowledge; developing safer, more effective treatments; educating the next generation of medical leaders and innovators; and supporting local communities by delivering high-quality care to all who need it. Through the integration of its hospitals, labs, and schools, Mount Sinai offers comprehensive health care solutions from birth through geriatrics, leveraging innovative approaches such as artificial intelligence and informatics while keeping patients' medical and emotional needs at the center of all treatment. The Health System includes more than 9,000 primary and specialty care physicians; 13 joint-venture outpatient surgery centers throughout the five boroughs of New York City, Westchester, Long Island, and Florida; and more than 30 affiliated community health centers. We are consistently ranked by U.S. News & World Report's Best Hospitals, receiving high "Honor Roll" status, and are highly ranked: No. 1 in Geriatrics, top 5 in Cardiology/Heart Surgery, and top 20 in Diabetes/Endocrinology, Gastroenterology/GI Surgery, Neurology/Neurosurgery, Orthopedics, Pulmonology/Lung Surgery, Rehabilitation, and Urology. New York Eye and Ear Infirmary of Mount Sinai is ranked No. 12 in Ophthalmology. U.S. News & World Report's "Best Children's Hospitals" ranks Mount Sinai Kravis Children's Hospital among the country's best in several pediatric specialties. The Icahn School of Medicine at Mount Sinai is ranked No. 11 nationwide in National Institutes of Health funding and in the 99th percentile in research dollars per investigator according to the Association of American Medical Colleges. Newsweek's "The World's Best Smart Hospitals" ranks The Mount Sinai Hospital as No. 1 in New York and in the top five globally, and Mount Sinai Morningside in the top 20 globally.
Equal Opportunity Employer
The Mount Sinai Health System is an equal opportunity employer, complying with all applicable federal civil rights laws. We do not discriminate, exclude, or treat individuals differently based on race, color, national origin, age, religion, disability, sex, sexual orientation, gender, veteran status, or any other characteristic protected by law. We are deeply committed to fostering an environment where all faculty, staff, students, trainees, patients, visitors, and the communities we serve feel respected and supported. Our goal is to create a healthcare and learning institution that actively works to remove barriers, address challenges, and promote fairness in all aspects of our organization.

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