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Full Time Statistics Postdoc information

What are the key skills and qualifications needed to thrive as a Full Time Statistics Postdoc, and why are they important?

A Full Time Statistics Postdoc requires advanced knowledge of statistical theory, research methodologies, and a Ph.D. in statistics or a related field. Experience with statistical programming languages such as R, Python, or SAS, as well as familiarity with data analysis software and reproducible research tools, is typically expected. Strong analytical thinking, problem-solving abilities, and effective communication skills distinguish standout candidates. These competencies are crucial for conducting high-level research, collaborating with interdisciplinary teams, and disseminating complex findings to diverse audiences.

What are Full Time Statistics Postdocs?

Full Time Statistics Postdocs are early-career researchers who have recently earned a Ph.D. in statistics or a closely related field and are employed in a full-time, temporary position at a university, research institute, or industry lab. Their primary focus is conducting advanced research, often collaborating with faculty members or research teams, and publishing their findings in academic journals. These positions are designed to help postdocs further develop their research skills, expand their academic network, and prepare for permanent roles in academia or industry.

What are the typical research and collaboration expectations for a Full Time Statistics Postdoc?

As a Full Time Statistics Postdoc, you'll typically engage in both independent and collaborative research projects, often working alongside faculty members and fellow postdocs. You may be expected to contribute to ongoing grant-funded studies, co-author publications, and present findings at conferences. Collaboration with interdisciplinary teams—including scientists, data analysts, and students—is common, fostering a dynamic learning environment. Balancing your own research interests with project goals is a common challenge, but it also provides valuable experience that can help you build a strong academic or industry career.

What is the difference between Full Time Statistics Postdoc vs Data Scientist?

AspectFull Time Statistics PostdocData Scientist
Required CredentialsPhD in Statistics, Mathematics, or related fieldBachelor's or Master's in Data Science, Computer Science, or related field; often prefers experience
Work EnvironmentAcademic or research institutions, universitiesCorporate, tech companies, or startups
Employer & Industry UsageResearch-focused roles in academia or governmentIndustry-focused roles in technology, finance, healthcare

Full Time Statistics Postdocs primarily work in academic or research settings, focusing on advanced statistical research and publications. Data Scientists work in industry, applying statistical and machine learning techniques to solve business problems. While both roles require strong statistical skills, Postdocs emphasize research and theory, whereas Data Scientists focus on practical data analysis and product development.

What are the most commonly searched types of Statistics Postdoc jobs in California? The most popular types of Statistics Postdoc jobs in California are:
What are popular job titles related to Full Time Statistics Postdoc jobs in California? For Full Time Statistics Postdoc jobs in California, the most frequently searched job titles are:
What job categories do people searching Full Time Statistics Postdoc jobs in California look for? The top searched job categories for Full Time Statistics Postdoc jobs in California are:
Full Time Statistics Postdoc jobs near you
Infographic showing various Full Time Statistics Postdoc job openings in California as of July 2026, with employment types broken down into 75% Full Time, 22% Part Time, and 3% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution.

Postdoctoral Scholar

Lawrence Berkeley National Laboratory

Berkeley, CA • On-site

Full-time

Medical, Retirement, PTO

Re-posted 14 days ago

Lawrence Berkeley National Laboratory rating

9.5

Company rating: 9.5 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

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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