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High Performance Computing Postdoc Jobs (NOW HIRING)

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High Performance Computing Postdoc information

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How much do high performance computing postdoc jobs pay per year?

As of Sep 13, 2026, the average yearly pay for high performance computing postdoc in the United States is $59,022.00, according to ZipRecruiter salary data. Most workers in this role earn between $49,000.00 and $66,500.00 per year, depending on experience, location, and employer.

What is a high performance computing postdoc?

A High Performance Computing (HPC) Postdoc is a researcher who has completed their doctoral studies and is engaged in advanced research involving the use of powerful computational systems to solve complex scientific, engineering, or data-intensive problems. These postdoctoral researchers develop, optimize, and implement algorithms and software on supercomputers, often collaborating with multidisciplinary teams. Their work may involve simulation, modeling, data analysis, or machine learning, and they contribute to scientific discovery through computational innovation.

What are the key skills and qualifications needed to thrive as a high performance computing postdoc?

To excel as a High Performance Computing Postdoc, you need a PhD in a relevant field, strong programming skills in languages like C/C++ or Fortran, and experience with parallel computing concepts. Familiarity with HPC clusters, job schedulers (e.g., SLURM), performance profiling tools, and possibly certifications in HPC systems are typical requirements. Excellent problem-solving, collaboration, and scientific communication skills help you work effectively within interdisciplinary research teams. These competencies are essential for advancing scientific discovery through efficient use of advanced computational resources and for contributing meaningfully to complex research projects.

What are some typical challenges high performance computing postdocs face when integrating new algorithms into existing HPC systems?

High Performance Computing Postdocs often encounter challenges related to optimizing new algorithms for compatibility and efficiency within established HPC infrastructures. These challenges may include ensuring code scalability across thousands of processors, managing memory bottlenecks, and adapting algorithms to diverse hardware architectures such as GPUs or distributed clusters. Collaboration with system administrators and other researchers is common, as troubleshooting and performance tuning require interdisciplinary expertise. Staying updated with evolving HPC technologies and best practices is essential for overcoming these integration hurdles.

What are popular job titles related to High Performance Computing Postdoc jobs?

For High Performance Computing Postdoc jobs, the most frequently searched job titles are:

Infographic showing various High Performance Computing Postdoc job openings in the United States as of September 2026, with employment types broken down into 71% Full Time, and 29% Contract. Highlights an 86% In-person, and 14% Remote job distribution, with an average salary of $59,022 per year, or $28.4 per hour.

High Performance Computing (HPC) Engineer

Oklahoma City, OK โ€ข On-site

Federal Reserve Bank of San Francisco
Public Administrationย โ€ขย 1 - 5K employees

Full-time

Re-posted 6 days ago


Job description

CompanyFederal Reserve Bank of Kansas CityWhen you join the Federal Reserve-the nation's central bank-you'll play a key role, collaborating with leading tech professionals to strengthen and protect our economic, financial and payments systems. We invest in contemporary and emerging technology each year to support the Federal Reserve and our economy, and we're building a dynamic and diverse team for our future.

Important Information

  • Open to US Citizens, Green Card holders or Permanent Residents with at least 3 years of residency, with the intent to become a US citizen.

  • No sponsorship is available. Candidates must have valid work authorization, without an end date, to be considered.

  • This position requires working on-site, in Kansas City, Denver, Oklahoma City or Omaha, with 5 days per month work from home flexibility. Relocation assistance is available.

About the Role

The Center for the Advancement of Data and Research in Economics (CADRE) supports data and computationally intensive research and analytics for staff in the Economic Research division of the Federal Reserve Bank of Kansas City and across the Federal Reserve System. Our services include multiple high performance computing environments, research data warehousing, and advanced analytical tools. We are an embedded technology team within the division of Economic Research, Regional, and Community Affairs.

We are seeking an experienced High Performance Computing Engineer who can plan, implement, and maintain advanced cyberinfrastructure solutions. The ideal candidate will have deep expertise in HPC architectures, parallel computing frameworks, and scientific computing applications. You will work independently while collaborating with researchers to solve complex computational challenges that support critical economic research initiatives.

Key Activities

Operations

  • Design, deploy, configure, and administer medium scale HPC clusters and associated storage systems.

  • Monitor system health, performance metrics, and resource utilization to ensure optimal operation.

  • Implement robust security protocols and perform regular maintenance including upgrades and patching.

  • Troubleshoot complex hardware and software issues in a multi-user research environment.

  • Manage job scheduling and workload optimization using tools like SLURM.

  • Administer parallel file systems (such as ceph and IBM Spectrum Scale/GPFS) and storage solutions.

Development

  • Design and implement innovative HPC solutions to address evolving research requirements.

  • Create and maintain automation scripts and tools to streamline system administration.

  • Optimize scientific applications and computational workflows for performance.

  • Implement container technologies (Docker, Singularity) for reproducible research.

  • Support GPU computing and accelerator technologies for specialized workloads.

  • Define and track performance metrics to ensure efficient current and future use of resources.

Partnership/Collaboration

  • Partner closely with researchers to understand computational needs and translate them into technical solutions.

  • Collaborate with network, security, and data center teams to ensure integrated operations.

  • Build and maintain relationships with external vendors and technology partners.

  • Participate in the HPC community to stay current with emerging technologies and best practices.

  • Serve as a technical advisor on infrastructure planning and technology roadmaps.

Documentation/Training

  • Develop comprehensive documentation for systems, policies, and procedures.

  • Create user guides and training materials for researchers utilizing HPC resources.

  • Provide mentorship to junior staff and knowledge sharing across teams.

  • Conduct workshops and training sessions on effective use of HPC resources.

Qualifications

Required

  • Bachelor's degree in computer science, engineering, mathematics, or related field, or equivalent combination of education and experience.

  • Minimum of 6 years of relevant experience in HPC administration and systems engineering.

  • Extensive experience with Linux operating systems (Red Hat/CentOS) in an HPC environment.

  • Strong command line skills and proficiency in scripting languages (Python, Bash).

  • Experience with job scheduling systems (SLURM, PBS, LSF) and resource management.

  • Knowledge of parallel file systems and storage technologies (e.g. ceph, GPFS, Lustre, BeeGFS).

  • Familiarity with parallel programming models (MPI, OpenMP) and scientific computing frameworks.

  • Experience with configuration management and automation tools (Salt, Ansible, Puppet).

  • Demonstrated problem-solving abilities and analytical thinking.

Preferred

  • Advanced degree in a computational field.

  • Experience with cloud computing platforms and hybrid HPC environments.

  • Experience with GitLab CI/CD pipelines for research software development.

  • Understanding of GPU computing and accelerator technologies (CUDA, OpenACC).

  • Experience supporting machine learning and AI workloads on HPC systems.

Additional Information

How We Work (HWW)

  • On-site: 5 days per month remote work flexibility

  • Location: Kansas City, Denver, Oklahoma City, or Omaha

  • Remote Eligible: No

  • Relocation Assistance: Yes

Salary

  • $110,300 - $155,700 / Senior Level

  • $125,200 - $176,700 / Advanced Level

  • $139,500 - $196,800 / Expert-Lead Level

  • Final offers are determined by factors including the candidate's qualifications, internal alignment considerations, district assignment, and geographic location.

Screening: US Citizens and Green Card holders or Permanent Residents with at least 3 years of residency, with the intent to become a US citizen. This position has additional screening requirements due to the information accessed while performing the job. These additional screenings would be initiated at the time of offer acceptance and could take up to a couple of months to be completed. You can begin work before the screening is completed; however, continued employment is contingent on acceptable screening results. The areas screened may include education/employment verification, criminal history, credit history, and reference checks.

Sponsorship: The Federal Reserve Bank of Kansas City will not sponsor a new applicant for employment authorization for this position. Applicants must be currently authorized to work in the United States without the need for visa sponsorship now or in the future.

About Us

  • Total Rewards & Benefits

  • Who We Are

  • What We Do

Follow us on LinkedIn, Instagram, X (formerly Twitter), and YouTube #KCFedIT

Full Time / Part TimeFull timeRegular / TemporaryRegularJob Exempt (Yes / No)YesJob CategoryInformation Technology Family GroupWork ShiftFirst (United States of America)

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Always verify and apply to jobs on Federal Reserve System Careers (https://rb.wd5.myworkdayjobs.com/FRS) or through verified Federal Reserve Bank social media channels.

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