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Bioinformatics Hpc Jobs (NOW HIRING)

IQVIA

Scientist II, Bioinformatics

Santa Fe, NM · On-site

Operate production sequencing workflows on AWS using S3, EC2, HPC or parallel compute, and pipeline ... PhD in Bioinformatics, Computational Biology, Computer Science, Molecular Biology, Immunology ...

IQVIA, Inc.

Scientist II, Bioinformatics

Santa Fe, NM · On-site

Operate production sequencing workflows on AWS using S3, EC2, HPC or parallel compute, and pipeline ... PhD in Bioinformatics, Computational Biology, Computer Science, Molecular Biology, Immunology ...

GDIT

HPC Engineer

Rockville, MD · Hybrid

$123K - $166K/yr

Bachelor's degree in computer science, engineering, scientific computing, bioinformatics, or a related field and at least 5 years of related experience. * Experience supporting Linux systems in HPC ...

Saviance

Senior Bioinformatics Software Engineer

The Senior Bioinformatics Software Engineer plays a critical technical role in the design ... HPC environments (e.g., SLURM, Kubernetes, GCP, Azure) • Exposure to workflow management ...

GDIT

HPC Administrator

Hamilton, MT · Hybrid

$88K - $115K/yr

Bachelor's degree in computer science, engineering, scientific computing, bioinformatics, or a related field and at least 5 years of related experience. * Experience working in Linux-based HPC or ...

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Bioinformatics Hpc information

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$59.5K

$94.5K

$149.5K

How much do bioinformatics hpc jobs pay per year?

As of Sep 12, 2026, the average yearly pay for bioinformatics hpc 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 HPC specialist?

A Bioinformatics HPC (High-Performance Computing) specialist is a professional who leverages powerful computing resources to analyze large biological datasets, such as genomic sequences or protein structures. They combine expertise in bioinformatics and computational science to build, optimize, and run complex data analysis pipelines on HPC clusters. Their work supports research in areas like genomics, drug discovery, and personalized medicine by enabling faster and more efficient data processing than would be possible on standard computers.

How does a bioinformatics HPC specialist typically collaborate with research scientists and software engineers on large-scale genomic projects?

Bioinformatics HPC professionals often serve as a bridge between research scientists and software engineers, ensuring that computational workflows run efficiently on high-performance computing clusters. They work closely with scientists to understand research objectives and translate them into scalable analyses, while collaborating with software engineers to optimize pipelines and troubleshoot technical issues. This role requires frequent communication to align computational resources with project needs and to adapt workflows as new data or research questions arise. Effective collaboration ensures both scientific rigor and computational efficiency in large-scale genomic studies.

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

To thrive as a Bioinformatics HPC specialist, you need strong expertise in computational biology, programming (e.g., Python, R), and a background in bioinformatics or computational science, often supported by a relevant degree. Familiarity with high-performance computing (HPC) environments, workflow management systems, and bioinformatics software tools like BLAST or GATK is essential. Analytical thinking, problem-solving, and effective collaboration are critical soft skills that set top performers apart. These skills and qualities are vital for efficiently processing large-scale biological data, developing reproducible pipelines, and driving impactful research in genomics and life sciences.

What is the difference between Bioinformatics Hpc vs Bioinformatics Analyst?

AspectBioinformatics HpcBioinformatics Analyst
Required CredentialsBachelor's or Master's in Bioinformatics, Computer Science, or related fields; experience with high-performance computingBachelor's or Master's in Bioinformatics, Biology, or related fields; data analysis skills
Work EnvironmentResearch labs, data centers, computational clustersResearch institutions, biotech companies, healthcare settings
Employer & Industry UsageResearch institutions, universities, biotech firms focusing on large-scale data processingHealthcare, pharmaceutical companies, research labs analyzing biological data

Bioinformatics Hpc specialists focus on managing and optimizing high-performance computing resources for large biological datasets, while Bioinformatics Analysts interpret biological data to generate insights. Both roles require strong computational skills, but Hpc roles emphasize infrastructure and system management, whereas Analysts focus on data analysis and interpretation.

What other helpful pages are available for Bioinformatics Hpc?

Other pages related to Bioinformatics Hpc:

Infographic showing various Bioinformatics Hpc job openings in the United States as of September 2026, with employment types broken down into 50% Full Time, and 50% Contract. Highlights an 100% In-person job distribution, with an average salary of $94,474 per year, or $45.4 per hour.

Bioinformatics Analyst

Bronx, NY • On-site

Albert Einstein College of Medicine
See more jobs at Albert Einstein College of Medicineexternal

Full-time

Re-posted 11 days ago

Job description

About Us
We are seeking a highly motivated Bioinformatics Analyst to join the research group of Dr. Robert Burk at Albert Einstein College of Medicine. Our group conducts molecular epidemiology and microbiome research with an emphasis on the human microbiome (cervicovaginal, oral, and gut) and HPV-related neoplasia. This role is central to translating large-scale sequencing datasets into rigorous, publication-ready results with direct relevance to chronic disease, cancer prevention and infectious disease research. Our work has been published in high-impact journals such as Nature Communications and Cell. The ideal candidate is an independent problem solver who is comfortable taking ownership of analysis workstreams, building and maintaining reproducible pipelines, and driving projects forward from raw data to interpretable outputs. They should be collaborative, communicate clearly with wet lab and epidemiology teams, and proactively propose analytic approaches that strengthen the science and accelerate progress.
POSITION RESPONSIBILITIES
  • Pipeline development and leadership: Design, implement, document, and maintain end-to-end NGS pipelines for microbiome and HPV genomics applications (e.g., 16S/ITS1 amplicon sequencing, shotgun metagenomics, viral/HPV sequencing, bisulfite sequencing, and viral integration analyses).
  • Large-scale data processing: Perform robust QC, read processing, reference alignment, taxonomic and functional profiling, strain-level analyses where appropriate, and reproducible reporting for cohort-scale datasets.
  • Clinical and epidemiologic integration: Harmonize sequencing outputs with clinical and epidemiologic metadata (including complex longitudinal designs), perform data cleaning and validation, and generate analysis-ready tables.
  • Statistical and computational analysis: Conduct and interpret statistical analyses using R and/or Python, including microbiome-specific methods (alpha/beta diversity, ordination, PERMANOVA, differential abundance) and epidemiologic modeling (regression and related approaches), with publication-quality visualizations.
  • Project leadership and communication: Lead defined analysis workstreams, set realistic milestones, communicate risks and dependencies early, and present progress and results in lab meetings and to collaborators.
  • Troubleshooting and optimization: Diagnose and resolve complex issues (pipeline failures, batch effects, contamination artifacts, inconsistent metadata, compute bottlenecks). Improve robustness, scalability, and runtime efficiency on shared compute environments.
  • Reproducibility and best practices: Use version control (Git), structured documentation, and reproducible execution practices (workflow managers and/or containerization when appropriate). Maintain clear provenance from raw data to results.
  • Scientific contribution: Propose fresh analytic ideas, evaluate new tools and methods, and contribute to interpretation and narrative framing of findings.
  • Manuscripts and grants: Contribute figures, methods text, and analyses for manuscripts and grant applications.

QUALIFICATIONS
Required:
  • Bachelor's degree in bioinformatics, computational biology, biostatistics, epidemiology, computer science, or a related field; Master's or PhD preferred.
  • Strong programming ability in R and/or Python, plus comfort working in a Unix/Linux environment (shell scripting, HPC-style workflows).
  • Demonstrated experience processing and analyzing NGS data, including building or extending pipelines rather than only running existing ones.
  • Solid understanding of basic statistical concepts and the ability to translate scientific questions into appropriate analyses.
  • Track record of independent problem solving, attention to detail, and producing reliable, well-documented outputs.
  • Strong communication skills and a collaborative mindset for working with interdisciplinary teams.

Preferred:
  • Experience in microbiome bioinformatics (16S, ITS1, shotgun metagenomics) and/or viral genomics with familiarity with phylogenetics, or integration-related analyses.
  • Experience working with protected clinical or epidemiologic data and with best practices for data security and governance.
  • Experience analyzing large cohorts and handling confounding, batch effects, and complex study designs (longitudinal, nested case-control, matched studies).
  • Comfort translating analyses into clear figures, methods, and results text suitable for high-impact manuscripts

Practical Experience: The candidate is expected to have practical experience with bioinformatics work (handling NGS reads off the machine, etc.) and be willing and eager to adapt to new approaches. This role will be facilitated with a proactive attitude towards learning and applying new bioinformatics methods and technologies.
Additional Information
In compliance with NYC's Pay Transparency Act, the annual base salary range for this position is listed below. Albert Einstein College of Medicine considers factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience, education/training, key skills, internal peer equity, as well as, market and organizational considerations when extending an offer.
Maximum Salary Range
USD $65,000.00/Yr.

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