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How much do postdoc in topological data jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for postdoc in topological data in Novato, CA is $38.83, according to ZipRecruiter salary data. Most workers in this role earn between $28.80 and $46.01 per hour, depending on experience, location, and employer.

What is a postdoc in topological data?

A Postdoc in Topological Data is a researcher who has completed their PhD and is engaged in advanced research focused on the application of topology—an area of mathematics dealing with spatial properties—to analyze and interpret complex data sets. These positions typically involve both theoretical work and the development of computational tools to extract meaningful patterns from high-dimensional or complex data. Postdocs in this field often collaborate with interdisciplinary teams in mathematics, computer science, and applied domains such as biology or engineering. The role is intended to deepen expertise, publish research, and prepare for academic or research-intensive careers.

What are the key skills and qualifications needed to thrive as a postdoc in topological data?

To thrive as a Postdoc in Topological Data, you need a strong background in mathematics (particularly topology, algebra, and geometry), data analysis, and a PhD in a related field. Familiarity with computational tools like Python, R, MATLAB, and software libraries for topological data analysis (such as GUDHI or Ripser) is typically required. Exceptional problem-solving ability, collaboration, and strong scientific communication skills help distinguish top candidates in interdisciplinary research environments. These skills are crucial for advancing research, publishing high-quality work, and contributing effectively to collaborative scientific projects.

What are some typical collaborative opportunities for a postdoc in topological data within academic or research settings?

As a Postdoc in Topological Data, you can expect to collaborate closely with interdisciplinary teams, including mathematicians, computer scientists, and domain experts from fields like biology or materials science. Collaborative projects often involve developing or applying topological methods to analyze complex datasets, contributing both theoretical insights and computational tools. These interactions may include co-authoring research papers, participating in joint seminars, and working with graduate students. Such collaborations not only broaden your research impact but also help expand your professional network and skill set.

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Infographic showing various Postdoc In Topological Data job openings in Novato, CA as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $80,770 per year, or $38.8 per hour.

Pantropical Vegetation Dynamics Postdoctoral Fellow

Lawrence Berkeley National Laboratory

Berkeley, CA • On-site

$6.5K - $8.9K/mo

Full-time

Medical, Retirement, PTO

Posted 9 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 121 rated laboratories

Job description

The Climate and Ecosystem Sciences Division at Berkeley Lab seeks a Pantropical Vegetation Dynamics Postdoctoral Fellow to combine observational synthesis, ecological theory, and numerical models to explore the dynamics of tropical forests responding and feeding back to climate. The position is part of the NGEE-Tropics project (https://ngee-tropics.lbl.gov), a long-term, DOE-funded effort to bring together observational and theoretical approaches to build, inform, and test the representation of tropical forests within Earth system models. NGEE-Tropics aims to fill the critical gaps in knowledge of tropical forest-climate system interactions, and works on cutting edge advancements in model predictions of tropical forest responses to a changing climate over the 21st Century.
We invite outstanding early career scientists to apply for a postdoctoral research position focused on Pantropical Vegetation Dynamics. The successful candidate will investigate processes associated with the large-scale structure and function of tropical forests, and how these are governed by plant traits as represented with a vegetation demography model. A central focus of this work is the study of mechanistic process-level controls on forest dynamics, including processes such as nutrient cycling and plant hydraulics, and how ecosystems respond to moisture and temperature stress, as well as anthropogenic and natural disturbances. The postdoctoral researcher will have the opportunity to develop and pursue hypothesis-driven research within the broader goals of the NGEE-Tropics project.
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:
  • Run and test the ELM-FATES (E3SM Land Model configured to include the Functionally Assembled Terrestrial Ecosystem Simulator) against multiple observational datasets at site to pantropical scales
  • Apply ecological and plant physiological theory to explore mechanistic process controls and plant trait variation on ecosystem structure and the large-scale exchange of carbon, water and energy for tropical forests.
  • Analyze complex datasets with the NGEE-Tropics data team, including eddy covariance, forest census, plant ecophysiology, remote sensing, land use/land cover change
  • Investigate land-atmosphere feedbacks at time scales ranging from hourly to centennial, including under a range of climate and land use change scenarios
  • Publish results in high-quality journals and contribute to proposals involving tropical biosphere-atmosphere interactions.
  • Participate and present results in meetings and conferences

We are looking for:
  • PhD in relevant field (e.g. climate science, ecology, plant physiology, forestry, geography)
  • Background in data intensive processing and analysis using open-source code (e.g., Python, R)
  • Demonstrated proficiency in code documentation and reproducibility, and collaboration platforms (e.g., GitHub, Jupyter Notebook, R Markdown)
  • An ability to understand and write land surface model code (e.g., FORTRAN) and interest in the application and testing of state-of-the-art land-surface models and/or Earth system models
  • Record of publishing research in peer-reviewed journals
  • Desire to work within an integrated, multi-institution team whose activities span from field research to Earth system model development

Desired skills/knowledge:
  • Solid background in ecological, plant physiological, and biogeochemical theory
  • We particularly encourage applicants with field experience or other backgrounds working in tropical forests
  • Availability to travel for meetings at partner institutions

For consideration, please apply with the following application materials:
  • CV
  • Cover letter
  • Research Statement

Additional information:
  • Application date: 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 monthly salary range for this position is $6,573 - $8,921 and is expected to start at $6,573 or above. Postdoc 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 and/or related research 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 will be primarily performed at: Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA. A REAL ID or other acceptable form of identification is required to access Berkeley Lab sites (for more information click here).
  • 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 final candidate who accepts an offer of employment will be required to disclose if they have been subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct; or have filed an appeal of a finding of substantiated misconduct with a previous employer. For additional information, click here.

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