NESAP for Machine Learning Postdoctoral Fellow jobs in United States
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Berkeley Lab · 1 day ago

NESAP for Machine Learning Postdoctoral Fellow

positionBay Area, California, United States
timeFull-time
remoteHybrid
seniorityNew Grad, Entry Level
money$8,570/mo - $9,935/mo

Berkeley Lab's NERSC is seeking a highly motivated Postdoctoral Researcher in Scientific Machine Learning to join their Workflow Readiness team. The role involves building AI-driven scientific workflows and collaborating with domain scientists and partners to prepare high-impact workflows for NERSC users.

Research
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H1B Sponsor Likelynote

Responsibilities

Contribute to one or more NESAP AI-based scientific workflows targeting NERSC HPC resources, edge resources, and the DOE ESnet network
Develop and apply advanced workflow capabilities to improve performance, portability, and productivity of scientific software
Collaborate with computational and domain scientists to integrate state-of-the-art AI with simulation and data analysis, including modern agentic approaches
Publish and present results in peer-reviewed venues
Development, performance analysis and optimization of end-to-end science workflows, including those originating at DOE facilities
Deployment of capabilities such as AI training and inference at scale, and tight AI-simulation coupling

Qualification

PythonC++TensorFlowPyTorchFortranJuliaGPU programmingDistributed trainingPerformance profiling toolsDebuggingContainersGitUnit testingCI/CDCollaborative developmentInterdisciplinary teamworkCommunication

Required

PhD in Physics, Chemistry, Computational Science, Data Science, Computer Science, Applied Mathematics, or a related numerical field
Programming experience in one or more of: Python, C++, Fortran, Julia
Hands-on experience building and training AI models with frameworks such as TensorFlow or PyTorch
Ability to succeed in an interdisciplinary team and communicate results clearly in writing and presentations

Preferred

Knowledge of GPU architecture and GPU programming
Interest or experience in distributed training on large scientific datasets and staying current with new training methods and architectures
Experience with performance and profiling tools such as Perftools, NVIDIA Nsight, AMD uProf, or Omniperf
Debugging experience with distributed-memory parallel applications
Experience with containers (Docker, Podman, Shifter or similar) and modern software practices such as Git, unit testing, CI/CD, and collaborative development
Publications in ML-for-Science, HPC, or systems venues (SC/ISC, PPoPP, IPDPS, MLSys, NeurIPS workshops)

Company

Berkeley Lab

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Berkeley Lab is a national laboratory that creates advanced new tools for scientific discovery.
dateFounded in 1931
location
Berkeley, California, USA
people-size1001-5000 employees
web-link
https://newscenter.lbl.gov/

H1B Sponsorship

Berkeley Lab has a track record of offering H1B sponsorships. Please note that this does not guarantee sponsorship for this specific role. Below presents additional info for your reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (154)
2024 (159)
2023 (163)
2022 (154)
2021 (165)
2020 (107)

Funding

Current Stage
Late Stage

Leadership Team

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Mary Barnum, MBA
Business Manager, COO Office
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Rebecca Rishell
Deputy Chief Operating Officer
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