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

As of Aug 12, 2026, the average hourly pay for postdoc in topological data in Ashburn, VA is $33.82, according to ZipRecruiter salary data. Most workers in this role earn between $25.10 and $40.05 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 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.

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.
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Infographic showing various Postdoc In Topological Data job openings in Ashburn, VA 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 $70,350 per year, or $33.8 per hour.

NIST PREP Postdoc in Decision-Science for a Circular Economy

Southeastern Universities Research Association

Gaithersburg, MD • On-site

$80K - $85K/yr

Full-time

Re-posted 17 days ago

Job description

This position is part of the National Institute of Standards and Technology (NIST) Professional Research Experience (PREP) program. NIST recognizes that its research staff may wish to collaborate with researchers at academic institutions on specific projects of mutual interest, thus requires that such institutions must be the recipient of a PREP award. The PREP program requires staff from a wide range of backgrounds to work on scientific research in many areas. Employees in this position will perform technical work that underpins the scientific research of the collaboration.
The position is in the Applied Economics Office (AEO), a part of the Engineering Laboratory (EL) at NIST, which provides economic products and services through research and consulting to industry and government agencies in support of productivity enhancement, economic growth, and international competitiveness, with a focus on improving the life-cycle quality and economy of constructed facilities and manufacturing processes that support social and economic functions. AEO is integrated within EL's major research thrusts. AEO delivers high quality research and tool development that informs and assists stakeholders in their decision-making processes.
Research Title: Decision-Science for a Circular Economy
The work will entail: We are seeking an experienced post-doctoral researcher to produce rigorous, publication-quality research on consumer perceptions and preferences in two projects that focus on the circular economy. This role requires deep expertise in advanced survey methodologies, experimental design, and statistical modeling. The ideal candidate has a strong research publication record and experience managing large-scale surveys data. The two projects the post-doctoral associate will support are focused on consumer preferences for battery electric vehicle information and consumer preference for circular plastic products.
Key responsibilities could include, but are not limited to, leading the following activities:
  • Design and implementation of quantitative research studies, including stated preference surveys and conjoint experiments.
  • Apply advanced discrete choice models, latent class models, clustering techniques, to uncover heterogeneous preferences and segment-specific insights.
  • Translate complex statistical outputs into clear, decision-relevant metrics such as willingness-to-pay, demand elasticities, and adoption likelihoods.
  • Ensure analytical rigor consistent with peer-reviewed academic standards.
  • Author and co-author peer-reviewed journal articles, conference papers and technical reports.
  • Work collaboratively with an inter-disciplinary team of researchers.

Qualifications
  • Ph.D. in Economics, Engineering, or a related quantitative field
  • Experienceconducting applied survey research and quantitative analysis
  • Demonstrated expertise in:
    • Survey design and implementation
    • Conjoint analysis and discrete choice modeling
    • Segmentation and clustering methods
  • Strong publication record inpeer-reviewed journals
  • Proficiency inR and statistical modeling tools (e.g., Mplus, SPSS); experience with GIS or visualization tools is a plus
  • Experience coding surveys in survey down or similar open-source survey tool
  • At least 3 peer-reviewed publications
  • At least one first authored peer-reviewed publication using survey data
  • Excellent writing and communication skills
  • Self-driven and capable of working independently with minimal supervision
  • Must be US Citizen

Privacy Act StatementAuthority: 15 U.S.C. § 278g-1(e)(1) and (e)(3) and 15 U.S.C. § 272(b) and (c)
Purpose: The National Institute for Standards and Technology (NIST) hosts the Professional Research Experience Program (PREP) which is designed to provide valuable laboratory experience and financial assistance to undergraduates, post-bachelor's degree holders, graduate students, master's degree holders, postdocs, and faculty.
PREP is a 5-year cooperative agreement between NIST laboratories and participating PREP Universities to establish a collaborative research relationship between NIST and U.S. institutions of higher education in the following disciplines including (but may not be limited to) biochemistry, biological sciences, chemistry, computer science, engineering, electronics, materials science, mathematics, nanoscale science, neutron science, physical science, physics, and statistics. This collection of information is needed to facilitate administrative functions of the PREP Program.
Routine Uses: NIST will use the information collected to perform the requisite reviews of the applications to determine eligibility, and to meet programmatic requirements. Disclosure of this information is also subject to all the published routine uses as identified in the Privacy Act System of Records Notices: NIST-1: NIST Associates.
Disclosure: Furnishing this information is voluntary. When you submit the form, you are indicating your voluntary consent for NIST to use of the information you submit for the purpose stated.
SURA is an Equal Opportunity Employer. We believe that no one should be discriminated against because of their differences, such as age, disability, ethnicity, gender, gender identity and expression, religion, or sexual orientation. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status, or any other basis as protected by federal, state, or local law.
PREP0004102

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