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What is an HPC postdoc?

HPC Postdocs, or High Performance Computing Postdoctoral Researchers, are scientists who have completed their PhD and are conducting advanced research that leverages powerful computational systems to solve complex problems. They often work at universities, research institutes, or national laboratories, focusing on developing new algorithms, optimizing code for supercomputers, or applying computational methods to scientific challenges. HPC Postdocs collaborate with interdisciplinary teams and may also provide support or training in HPC techniques for other researchers. Their work is essential for pushing the boundaries of science in fields such as physics, climate modeling, computational biology, and engineering.

What skills and qualifications are needed to thrive as an HPC postdoc?

To thrive as an HPC Postdoc, you need advanced knowledge in computational science, parallel programming, and a relevant doctoral degree, often in fields like physics, computer science, or engineering. Expertise in programming languages (such as C/C++, Fortran, Python), experience with high-performance computing systems, and familiarity with tools like MPI, OpenMP, or GPU computing frameworks are typically required. Strong analytical thinking, problem-solving, and collaboration skills set outstanding candidates apart in research environments. These competencies are crucial for conducting cutting-edge research, optimizing complex simulations, and advancing scientific discovery using supercomputing resources.

What are common challenges faced by an HPC postdoc when optimizing scientific applications for supercomputing environments?

HPC Postdocs often encounter the challenge of adapting complex scientific codes to efficiently utilize advanced supercomputing architectures. This may involve addressing issues such as parallel scalability, memory bottlenecks, and compatibility with different hardware or software environments. Collaborating closely with domain scientists, software engineers, and IT staff is essential to troubleshoot performance issues and implement effective solutions. Staying up-to-date with emerging HPC technologies and optimization techniques is also crucial for success in this role.
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Infographic showing various Hpc Postdoc job openings in the United States as of August 2026, with employment types broken down into 100% Full Time. Highlights an 57% In-person, and 43% Hybrid job distribution.

Postdoctoral Scholar

Lawrence Berkeley National Laboratory

Berkeley, CA • On-site

Full-time

Medical, Retirement, PTO

Re-posted 27 days ago

Lawrence Berkeley National Laboratory rating

9.5

Company rating: 9.5 out of 10

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2nd of 120 rated laboratories

Job description

Berkeley Lab's Center for Advanced Mathematics for Energy Research Applications (CAMERA) has a new opening for a postdoctoral scholar to develop cutting-edge mathematics and algorithms to analyze complex data from Department of Energy (DOE) experimental facilities.
This role involves research and development spanning areas such as optimization, Fourier analysis, numerical linear algebra, statistics, machine learning, and high-performance computing for one or more of the following: (1) reconstruction of 3D+ structure, heterogeneity, and/or dynamics from scattering and/or microscopy data; (2) autonomous analysis and decision making for self-driving and/or human-in-the-loop experiments; (3) computer vision for extracting complex patterns, structure, and meaning from images and/or volumes; and (4) new mathematics and algorithms leading to new applications of machine learning and artificial intelligence to analysis of experimental data. Of particular interest will be new approaches for tackling multimodal data, quantifying uncertainty, providing rigorous theoretical guarantees, and modelling complex physics, noise processes, and measurement error. You will work closely with mathematicians, software engineers, physicists, materials scientists, and beamline scientists to implement these new tools on HPC computer architectures and deliver them as user-friendly software to meet DOE experimental facility needs.
We're here for the same mission, to bring science solutions to the world. Join our team and YOU will play a supporting role in our goal to address global challenges! Have a high level of impact and work for an organization associated with 17 Nobel Prizes!
Why join Berkeley Lab?
We invest in our employees by offering a total rewards package you can count on:
  • Exceptional health and retirement benefits, including pension or 401K-style plans
  • A culture where you'll belong - we are invested in our teams!
  • In addition to accruing vacation and sick time, we also have a Winter Holiday Shutdown every year.
  • Parental bonding leave (for both mothers and fathers)

You will:
  • Conduct independent and collaborative research to develop new mathematics and algorithms for analyzing complex data from DOE experimental facilities.
  • Develop new mathematical algorithms targeting one or more focus areas: (1) 3D+ reconstruction of structure/heterogeneity/dynamics from scattering and/or microscopy data; (2) autonomous analysis and decision-making for self-driving and/or human-in-the-loop experiments; (3) computer vision for extracting patterns, structure, and meaning from images and/or volumes; and (4) new mathematics and algorithms that enable new reliable new applications of machine learning and artificial intelligence to experimental data analysis.
  • Make advances in one or more of: multimodal data fusion/joint inference; uncertainty quantification with realistic noise/measurement error; complex physics- and artifact-aware forward modeling; and theory-grounded guarantees for proposed algorithms.
  • Collaborate with scientific users and experimentalists at DOE experimental facilities to apply the developed software to real datasets and meet their scientific needs.
  • Publish results in peer-reviewed venues, present at conferences/workshops, and contribute to CAMERA's collaborative research activities.

We are looking for:
  • Ph.D. in Applied Mathematics, Computer Science, Physics, or related field.
  • Strong research track record developing advanced mathematical and computational methods for analyzing complex experimental or imaging data.
  • Demonstrated expertise in several of the following areas: inverse problems, statistics, optimization, uncertainty quantification, and/or computer vision/machine learning.
  • Strong foundation in at least one of: numerical linear algebra, Fourier/spectral methods, scientific computing, and/or high-performance computing.
  • Proven ability to publish in peer-reviewed venues and present research at seminars, workshops, and scientific conferences.
  • Excellent written and verbal communication skills, with the ability to contribute effectively to large, collaborative, multidisciplinary projects in a diverse environment.

Desired skills/knowledge:
  • Familiarity with modern machine learning methods and software, including experience applying them to scientific or experimental datasets.
  • Experience collaborating with domain scientists to analyze real experimental data and translate scientific questions into robust, actionable computational approaches.

Additional information:
  • Applications will be accepted until the job posting is removed.
  • Appointment type: This is a full-time, 2 year, postdoctoral appointment with the possibility of renewal based upon satisfactory job performance, continuing availability of funds and ongoing operational needs. You must have less than 3 years of paid postdoctoral experience. Salary for Postdoctoral positions depends on years of experience post-degree.
  • Salary range: The salary range for this position is $8,570 - $9,935 and is expected to start at $8,570 or above. Postdoctoral positions are paid on a step schedule per union contract and salaries will be predetermined based on postdoctoral step rates. Each step represents one full year of completed post-Ph.D. postdoctoral experience.
  • Background check: This position is subject to a background check. Any convictions will be evaluated to determine if they directly relate to the responsibilities and requirements of the position. Having a conviction history will not automatically disqualify an applicant from being considered for employment.
  • Work modality: Work may be performed on-site, hybrid. The primary location for this role is Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA. Work must be performed within the United States.
  • Union Represented: This position is represented by a union for collective bargaining purposes.

Want to learn more about working at Berkeley Lab? Please visit: careers.lbl.gov
Equal Employment Opportunity Employer: The foundation of Berkeley Lab is our Stewardship Values: Team Science, Service, Trust, Innovation, and Respect; and we strive to build community with these shared values and commitments. Berkeley Lab is an Equal Opportunity Employer. We heartily welcome applications from all who could contribute to the Lab's mission of leading scientific discovery, excellence, and professionalism. In support of our rich global community, all qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected categories under State and Federal law.
Misconduct Disclosure Requirement: As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct, are currently being investigated for misconduct, left a position during an investigation for alleged misconduct, or have filed an appeal with a previous employer.

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