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Postdoctoral In Bayesian Statistics Jobs in Washington, DC

Umd

Postdoctoral Associate

College Park, MD

$75K - $80K/yr

PhD in Computer Science or a closely-related field Experience: Experience in performing independent ... statistical inference (e.g. generative graphical models, maximum likelihood inference, Bayesian ...

Varsity Tutors

Statistics Graduate Level Tutor

Laurel, MD · Remote

$18 - $40/hr

... In a Statistics Graduate Level Tutor * Advanced Subject Mastery: Deep knowledge of mathematical statistics, maximum likelihood estimation, sufficient statistics, hypothesis testing theory, Bayesian ...

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Postdoctoral In Bayesian Statistics information

See Washington, DC salary details

$28.3K

$66.8K

$94.6K

How much do postdoctoral in bayesian statistics jobs pay per year?

As of Aug 20, 2026, the average yearly pay for postdoctoral in bayesian statistics in Washington, DC is $66,848.00, according to ZipRecruiter salary data. Most workers in this role earn between $55,500.00 and $75,300.00 per year, depending on experience, location, and employer.

What is a postdoctoral position in Bayesian statistics?

A Postdoctoral position in Bayesian Statistics is a research-focused role for individuals who have recently completed their PhD in statistics, mathematics, or a related field. These positions involve conducting advanced research using Bayesian methods, which apply probability to infer statistical conclusions. Postdocs often work on developing new Bayesian models, collaborating on interdisciplinary projects, and publishing research findings. Such positions are typically temporary and designed to further prepare researchers for academic, industry, or governmental roles.

What are the key skills and qualifications needed to thrive as a postdoctoral researcher in Bayesian statistics?

To thrive as a Postdoctoral Researcher in Bayesian Statistics, you need an advanced degree (typically a PhD) in statistics or a related field, with strong expertise in Bayesian inference and probabilistic modeling. Proficiency with statistical programming languages such as R, Python, or Stan, and experience with specialized Bayesian analysis software are highly valued. Excellent problem-solving skills, collaboration, and the ability to communicate complex statistical concepts clearly are standout soft skills for this role. These skills and qualities are crucial for conducting rigorous research, publishing impactful results, and contributing effectively to scientific teams.

What are some common challenges faced by postdoctoral researchers in Bayesian statistics, and how can they be addressed?

Postdoctoral researchers in Bayesian statistics often encounter challenges such as managing complex, high-dimensional data, staying current with rapidly evolving computational methods, and balancing independent research with collaborative projects. Effective strategies include leveraging open-source statistical software, actively participating in seminars and workshops to stay updated, and establishing regular communication with interdisciplinary teams. Building a strong professional network and seeking mentorship within the department can also help in navigating research obstacles and advancing one's career.

What is the difference between Postdoctoral In Bayesian Statistics vs Postdoctoral In Data Science?

AspectPostdoctoral In Bayesian StatisticsPostdoctoral In Data Science
Required CredentialsPhD in Statistics, Mathematics, or related fieldPhD in Computer Science, Statistics, or related field
Work EnvironmentAcademic research, university labsResearch institutions, tech companies, industry labs
Employer & Industry UsageUniversities, research institutesTech firms, finance, healthcare, consulting
Common Search & Comparison IntentSpecialized research roles in Bayesian methodsBroader data analysis and machine learning roles

Postdoctoral In Bayesian Statistics focuses on advanced research in Bayesian methods within academic settings, requiring deep statistical expertise. In contrast, Postdoctoral In Data Science covers a broader range of data analysis techniques, including machine learning, often in industry environments. Both roles require a PhD but differ in application focus and work environment.

What are popular job titles related to Postdoctoral In Bayesian Statistics jobs in Washington, DC?

For Postdoctoral In Bayesian Statistics jobs in Washington, DC, the most frequently searched job titles are:

What job categories do people searching Postdoctoral In Bayesian Statistics jobs in Washington, DC look for?

The top searched job categories for Postdoctoral In Bayesian Statistics jobs in Washington, DC are:

Postdoctoral In Bayesian Statistics jobs near you
Infographic showing various Postdoctoral In Bayesian Statistics job openings in Washington, DC as of August 2026, with employment types broken down into 76% Full Time, 21% Part Time, 1% Temporary, and 2% Contract. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution, with an average salary of $66,848 per year, or $32.1 per hour.

Post doctoral researcher in Statistics

University of Maryland Baltimore County

Baltimore, MD • On-site

Full-time

Re-posted 6 days ago

Job description

Description
The Department of Mathematics and Statistics at the University of Maryland, Baltimore County (UMBC) has an opening for a postdoctoral scholar position, starting in fall 2025, preferably with an interest or focus on "Foundations of digital twins and uncertainty quantification, with applications to neuroscience problems."
The appointment is for a fixed term, but renewable upon satisfactory performance and funding availability. Candidates should have finished their Ph.D. in statistics, biostatistics, machine learning, or a related field before their appointment start date. Successful candidates are expected to conduct research, collaborate with faculty members, apply for external funding, and teach courses.
Qualifications
Candidates in all areas of statistics and data science may apply. Our interests include but are not limited to high-dimensional statistics; Bayesian statistics; resampling techniques; digital twins; uncertainty quantification; statistical process control; foundations of machine learning and artificial intelligence; optimization theory and numerical optimization with applications to data science; statistical applications to biomedical problems and precision medicine.
Application Instructions
Applicants should apply using: http://apply.interfolio.com/158801
Applicants should submit (a) a cover letter; (b) a curriculum vitae that includes publications; (c) a description of research interests and research plans; (d) a brief teaching statement; (e) a statement of commitment to inclusive excellence; and (e) have at least three letters of recommendation submitted on their behalf.
Equal Employment Opportunity Statement
UMBC is an Equal Opportunity/Affirmative Action Employer.

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