Postdoctoral Scholar

Postdoctoral Scholar Opportunity at Berkeley Lab's CAMERA

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 modeling 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 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.