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Lawrence Berkeley National Laboratory

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Postdoctoral Scholar in Applied Mathematics and Computational Research Lawrence Berkeley National Laboratory in United States

Degree Level

Postdoc

Field of study

Computer Science

Funding

Full-time 2-year postdoctoral appointment with salary on a union step schedule; monthly salary range $8,827-$10,234, expected to start at $8,570 or above, with possible renewal based on performance, funding, and operational needs.

Deadline

Apr 26, 2027

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Country

United States

University

Lawrence Berkeley National Laboratory

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Keywords

Computer Science
Materials Science
Mathematics
Computational Science
Uncertainty Analysis
Linear Algebra
Fourier Analysis
High Performance Computing
Optimisation
Data Reconstruction
Statistics
Inverse Problem
Physics
Applied Mathematic
ML

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About this position

Lawrence Berkeley National Laboratory’s Center for Advanced Mathematics for Energy Research Applications (CAMERA) is seeking a postdoctoral scholar in its Applied Mathematics and Computational Research division. The position focuses on developing new mathematics, algorithms, and software for analyzing complex data from Department of Energy experimental facilities.

The research spans optimization, Fourier analysis, numerical linear algebra, statistics, machine learning, and high-performance computing. The scholar will work on one or more of several research directions, including reconstruction of 3D+ structure, heterogeneity, and dynamics from scattering or microscopy data; autonomous analysis and decision-making for self-driving experiments; agentic methods for extracting patterns and meaning from images and volumes; and new mathematical approaches that extend machine learning and artificial intelligence for experimental data analysis.

The role emphasizes multimodal data fusion, uncertainty quantification, physically realistic forward modeling, and theory-grounded algorithmic guarantees. The successful candidate will collaborate with mathematicians, software engineers, physicists, materials scientists, and beamline scientists to translate methods into user-friendly software on HPC architectures for DOE facility users.

The appointment is embedded in Berkeley Lab’s collaborative research environment and is aimed at producing methods that can be applied to real experimental datasets and shared through peer-reviewed publications and scientific presentations.

Funding details

Full-time 2-year postdoctoral appointment with salary on a union step schedule; monthly salary range $8,827-$10,234, expected to start at $8,570 or above, with possible renewal based on performance, funding, and operational needs.

What's required

Ph.D. in Applied Mathematics, Computer Science, Physics, or a 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, LLM, VLM, MCP, and/or agent-based 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. Familiarity with modern machine learning methods and software, especially for scientific or experimental datasets, and experience collaborating with domain scientists are desired.

How to apply

Apply directly online through the provided MathJobs listing. Follow the on-line instructions to complete the application process.

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