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Bioinformatics Gwas Jobs (NOW HIRING)

UAB NOVA RENT

Bioinformatician I (Temp)

Birmingham, AL · On-site

... GWAS) or NGS studies, performing downstream analyses, and recommending, creating and maintaining local bioinformatics databases, as well as making proper use of public databases. May convert study ...

University of Michigan

RESEARCH FELLOW

Ann Arbor, MI · On-site

We are a computationally focused lab in the Departments of Computational Medicine & Bioinformatics, Human Genetics, and Biostatistics, working at the interface of GWAS, single-cell multi-omics, and ...

Odyssey Therapeutics, Inc.

Develop, maintain, and optimize robust bioinformatics pipelines for the analysis of multi-omics datasets. * Analyze GWAS, eQTL, transcriptomic, proteomic, and other human disease datasets to identify ...

LatchBio

AI Biologist - Variant

San Francisco, CA · On-site +1

$120K - $180K/yr

Bioinformatics Engineer - Variant As molecular data generation and frontier model intelligence ... variant calling, GWAS, causal inference, and multiomics integration. Your benchmarks and ...

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Bioinformatics Gwas information

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$59.5K

$94.5K

$149.5K

How much do bioinformatics gwas jobs pay per year?

As of Sep 10, 2026, the average yearly pay for bioinformatics gwas in the United States is $94,474.00, according to ZipRecruiter salary data. Most workers in this role earn between $67,500.00 and $129,500.00 per year, depending on experience, location, and employer.

What is a bioinformatics GWAS?

A Bioinformatics GWAS (Genome-Wide Association Study) is a research approach that uses computational and statistical methods to analyze genetic data from many individuals to find associations between genetic variants and traits or diseases. Bioinformatics specialists working with GWAS are responsible for handling large datasets, running analyses to identify significant genetic markers, and interpreting the results in a biological context. This work helps to understand the genetic basis of complex traits and can inform medical research, drug development, and personalized medicine.

What are some typical challenges faced by bioinformaticians working on GWAS projects, and how can they be addressed?

Bioinformaticians working on GWAS (Genome-Wide Association Studies) often encounter challenges such as handling large-scale genomic data, ensuring data quality, and managing computational resources efficiently. Another common hurdle is the interpretation of statistically significant variants, which requires both biological insight and advanced analytical skills. Collaborating closely with geneticists, statisticians, and clinicians is crucial for overcoming these challenges, as interdisciplinary teamwork helps validate findings and integrate them into meaningful biological contexts.

What are the key skills and qualifications needed to thrive as a bioinformatics GWAS specialist, and why are they important?

To thrive as a Bioinformatics GWAS specialist, you need a strong background in genetics, statistics, and computer science, typically supported by a relevant degree such as bioinformatics or computational biology. Proficiency in programming languages like Python or R, experience with GWAS analysis pipelines, and familiarity with genomic databases are essential. Attention to detail, analytical thinking, and effective communication are crucial soft skills for interpreting complex data and collaborating with research teams. These skills enable accurate identification of genetic associations, effective data analysis, and impactful contributions to genomic research.

What is the difference between Bioinformatics Gwas vs Bioinformatics Analyst?

AspectBioinformatics GwasBioinformatics Analyst
Required CredentialsBachelor's or Master's in Bioinformatics, Genetics, or related fields; experience with GWAS toolsBachelor's or Master's in Bioinformatics, Computer Science, or related fields; programming skills
Work EnvironmentResearch labs, academic institutions, biotech companiesResearch institutions, healthcare, biotech firms
Employer & Industry UsageGenetics research, disease association studiesData analysis, software development, data management
Common Search & Comparison IntentUnderstanding GWAS-specific roles within bioinformaticsGeneral bioinformatics data analysis roles

Bioinformatics Gwas specialists focus on genome-wide association studies, analyzing genetic variants linked to traits or diseases. Bioinformatics Analysts have broader roles in data processing and analysis across various projects. While both require bioinformatics skills, Gwas roles are more specialized in genetic association research, whereas Analysts handle diverse bioinformatics tasks.

What other helpful pages are available for Bioinformatics Gwas?

Other pages related to Bioinformatics Gwas:

Infographic showing various Bioinformatics Gwas job openings in the United States as of September 2026, with employment types broken down into 86% Full Time, 12% Part Time, and 2% Contract. Highlights an 75% Physical, 4% Hybrid, and 21% Remote job distribution, with an average salary of $94,474 per year, or $45.4 per hour.

Bioinformatics Workflow Developer

South San Francisco, CA • On-site

Astrix Inc
Recruiting and Staffing Services • 1 - 5K employees
Learn more about Astrix Incexternal

$40 - $45/hr

Contractor

This job post has expired today. Applications are no longer accepted.

Job description

Pay Rate Low: 40 | Pay Rate High: 45
Our client is a leading biotechnology company seeking a Bioinformatics Workflow Developer to support computational research and drug discovery initiatives.
Title: Bioinformatics Workflow Developer
Duration: 12-Month Contract | W2 + Benefits
Location: US Remote | PST Hours
Pay Rate: $40-45/hr
Position Overview
This role will develop and optimize reproducible, scalable bioinformatics workflows for large-scale biological datasets, working closely with computational scientists, biomarker researchers, and experimental biologists.
Key Responsibilities
  • Develop, maintain, and productionize bioinformatics workflows using Nextflow, WDL, CWL, or Snakemake.
  • Analyze bulk and single-cell transcriptomic and epigenetic datasets, including RNA-seq, GWAS, proteomics, and perturbational data.
  • Build computational tools, libraries, statistical models, and visualizations to support biological research.
  • Deploy workflows across HPC and cloud environments.
  • Leverage AI/LLM tools and agentic coding workflows to improve development and analysis efficiency.
  • Communicate computational findings through Jupyter/R Notebooks, visualizations, and presentations.
  • Maintain strong standards for reproducibility, documentation, and data stewardship.

Qualifications
  • Bachelor's degree or higher in Bioinformatics, Computational Biology, Genomics, Systems Biology, Statistics, or a related field.
  • MUST be authorized to work for a US employer without sponsorship.
  • 2-5+ years of experience working with large-scale biological or clinical datasets.
  • Strong Python and/or R skills; experience with Scanpy, AnnData, Pandas, scikit-learn, ggplot2, and/or Bioconductor.
  • Hands-on experience with Nextflow, WDL, CWL, or Snakemake.
  • Experience with Linux, HPC, Git, and cloud environments.
  • Familiarity with AI/LLM-assisted development, including agentic coding or automated refactoring.
  • Knowledge of FAIR data principles and containerization using Docker, Singularity, or Apptainer.
  • Strong problem-solving, communication, and cross-functional collaboration skills.

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