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Mathematical Modeling Postdoc Jobs in Maryland (NOW HIRING)

Umd

Post-Doctoral associate

College Park, MD

$65K - $80K/yr

D. in Computer Science, Mathematics, or a related field with a strong computer systems or AI ... Experience with parallel programming models and languages (e.g. MPI, OpenMP, CUDA, Kokkos ...

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Mathematical Modeling Postdoc information

What is the difference between Mathematical Modeling Postdoc vs Data Scientist?

AspectMathematical Modeling PostdocData Scientist
Required CredentialsPhD in Mathematics, Applied Mathematics, or related fieldBachelor's or Master's in Data Science, Computer Science, or related field; PhD preferred
Work EnvironmentAcademic research institutions, universities, research labsCorporate, tech companies, startups, or consulting firms
Industry UsageResearch projects, academic publications, grant-funded studiesBusiness analytics, product development, data-driven decision making
Common Search & ComparisonYesYes

While both roles involve analytical skills and data handling, Mathematical Modeling Postdocs focus on academic research and developing theoretical models, whereas Data Scientists apply data analysis techniques to solve practical business problems. The choice depends on whether you prefer research-oriented work or industry applications.

What does a mathematical modeling postdoc do?

A Mathematical Modeling Postdoc conducts advanced research using mathematical techniques to analyze and solve complex real-world problems in fields such as biology, engineering, physics, or social sciences. They typically develop and apply mathematical models, run simulations, analyze data, and interpret results to support scientific or industrial projects. Postdocs in this role often collaborate with interdisciplinary teams, publish research findings, and may also assist in mentoring students or contributing to grant proposals.

What are some common challenges faced by mathematical modeling postdocs when transitioning from academic research to collaborative industry projects?

Mathematical Modeling Postdocs often encounter challenges when moving from academic research to industry settings, particularly in adapting to faster-paced timelines and working within interdisciplinary teams. In industry, projects may require quick prototyping and the ability to communicate complex mathematical concepts to non-experts, such as engineers or business stakeholders. Building effective collaborations and aligning research goals with organizational objectives can also be a significant adjustment. However, these challenges provide valuable experience and broaden career prospects in both academia and industry.

What are the key skills and qualifications needed to thrive as a mathematical modeling postdoc?

A Mathematical Modeling Postdoc requires an advanced degree (typically a PhD) in mathematics, applied mathematics, or a related quantitative field, along with strong analytical and problem-solving abilities. Expertise with programming languages such as Python, MATLAB, or R, and experience with simulation software or computational tools, are commonly expected. Strong communication, collaboration, and critical thinking skills help in presenting findings and working effectively within research teams. These competencies are vital for developing robust models, interpreting complex data, and contributing to innovative research outcomes.

What are popular job titles related to Mathematical Modeling Postdoc jobs in Maryland?

For Mathematical Modeling Postdoc jobs in Maryland, the most frequently searched job titles are:

What job categories do people searching Mathematical Modeling Postdoc jobs in Maryland look for?

The top searched job categories for Mathematical Modeling Postdoc jobs in Maryland are:

What cities in Maryland are hiring for Mathematical Modeling Postdoc jobs?

Cities in Maryland with the most Mathematical Modeling Postdoc job openings:

Mathematical Modeling Postdoc jobs near you
Infographic showing various Mathematical Modeling Postdoc job openings in Maryland as of August 2026, with employment types broken down into 88% Full Time, and 12% Part Time. Highlights an 95% In-person, 2% Hybrid, and 3% Remote job distribution.

NIST PREP Postdoc Associate in Process Modeling using Physically Informed Machine Learning

Southeastern Universities Research Association

Gaithersburg, MD • On-site

$84K - $92K/yr

Full-time

Re-posted 14 days ago

Job description

This position is part of the National Institute of Standards (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 and thus requires that such institutions be the recipients 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.
Research Title: Process Modeling using Physically Informed Machine Learning
The work will entail:
  • Designing and training physics-informed machine learning (PIML) models for the prediction of physical and chemical properties using data from experiments and computation constrained by physics requirements.
  • Implementing algorithms to assess the performance of PIML models.
  • Assessing uncertainty in the predictions of PIML models.
  • Developing systems for multiscale modeling of atomic layer deposition processes.
  • Developing software to implement the goals stated above (most likely in Python).
  • Disseminating results through posters/seminars and international meetings and meeting seminars.
  • Ensuring that all results, findings, data, software, etc. are correctly archived and transmitted through appropriate channels.

U.S. Citizen Preferred
Key responsibilities will include but are not limited to:
  • Algorithm development, implementation, and analysis
  • Analyze heterogeneous data sources.
  • Presenting results at internal meetings, and occasional meetings with external stakeholders.
  • Ensuring that results, protocols, software, and documentation have been archived or otherwise transmitted to the larger organization.

Qualifications
  • A Ph.D degree in Chemistry, Physics, Mathematics, Computer Science, Data Science, or a related field.
  • Significant course work in one or more of chemistry, physics, mathematics, statistics and/or computer science.
  • Familiarity with one or more chemical process modeling packages (e.g. Cantera, CHEMKIN).
  • Familiarity with one or more AI/ML software packages (e.g. Tensorflow or Pytorch).
  • Ability to program in a modern computational language (e.g. Python).
  • Strong oral and written communication skills.

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.
PREP0003547

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