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Postdoc In Topological Data Jobs in Reston, VA (NOW HIRING)

Esri

Sr. Technical Consultant- Defense

Fort Belvoir, VA · On-site

$107K - $183K/yr

Knowledge in modeling and managing logical and topological network data * System administration experience on Windows * Active TS Security Clearance with SCI eligibility * Bachelor's degree in ...

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

As of Jul 22, 2026, the average hourly pay for postdoc in topological data in Reston, VA is $34.41, according to ZipRecruiter salary data. Most workers in this role earn between $25.53 and $40.77 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, and why are they important?

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 job categories do people searching Postdoc In Topological Data jobs in Reston, VA look for? The top searched job categories for Postdoc In Topological Data jobs in Reston, VA are:
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NIST PREP Postdoc Associate Applying Machine Learning Methodologies to Predict Spectra of PFAS

NIST PREP Postdoc Associate Applying Machine Learning Methodologies to Predict Spectra of PFAS

Southeastern Universities Research Association

Gaithersburg, MD • On-site

$90K - $110K/yr

Full-time

Re-posted 5 days ago

Job description

This position is part of the National Institute of Standards and Technology (NIST) Professional Research Experience Program (PREP). NIST recognizes that its research staff may want to collaborate with researchers at academic institutions on specific projects of mutual interest and, therefore, requires those institutions to be recipients of a PREP award. The PREP program involves staff from a wide range of backgrounds conducting scientific research across various fields. Individuals in this position will perform technical work supporting the collaboration's scientific research.
Research Title: Postdoctoral Researcher Applying Machine Learning Methodologies to Predict Spectra of PFAS Compounds
The work will entail: The Materials Measurement Laboratory of the National Institute of Standards and Technology is seeking qualified persons (U.S. Citizens preferred) to apply modern methods in artificial intelligence (AI) and machine learning (ML) to the problem of predicting infrared spectra and mass spectra for PFAS compounds. The candidate should have a strong background in AI/ML with application to chemical problems, have familiarity with infrared and mass spectra, and understand the relevant chemistry of PFAS molecules. This position will involve working with a team of chemists, physicists, mathematicians, data scientists and machine learning experts characterizing PFAS molecules used in the semiconductor industry with the goal of discovering new molecules for the semiconductor etching process.
U.S. Citizen Preferred
Key responsibilities will include but are not limited to:
  • Develop libraries of training data through mining of existing databases and simulation of infrared and mass spectra using quantum chemistry and related methodologies.
  • Create AI/ML models for high-fidelity prediction of the infrared and mass spectra and validate their use in matching experimentally measured spectra.
  • Collaborate with other computational and experimental researchers to meet project goals.
  • Disseminate results through publications, talks, poster presentations, etc.

Qualifications
  • PhD. in chemistry, physics, or a closely aligned field.
  • Demonstrated experience in conducting quantum scattering calculations.
  • Strong programming skills in languages such as Python or C/C++, experience using modern software frameworks for AI/ML, and experience in data analysis.
  • Motivated, independent researcher with good organizational, communication and leadership skills.
  • Solid track-record of scientific publication.

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 the 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. By applying to a CHIPS-funded PREP opportunity, you also acknowledge that participation in the project requires signing a Non-Disclosure Agreement (NDA) prior to beginning any work.
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.
PREP0004008 or PREP0003620

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