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Postdoctoral In Bayesian Statistics information

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$24.3K

$57.3K

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

As of Jul 14, 2026, the average yearly pay for postdoctoral in bayesian statistics in Pittsburgh, PA is $57,299.00, according to ZipRecruiter salary data. Most workers in this role earn between $47,600.00 and $64,600.00 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 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 the key skills and qualifications needed to thrive as a Postdoctoral Researcher in Bayesian Statistics, and why are they important?

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.
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Postdoctoral In Bayesian Statistics jobs near you
Infographic showing various Postdoctoral In Bayesian Statistics job openings in Pittsburgh, PA as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $57,299 per year, or $27.5 per hour.
Postdoctoral Research Associate - Yttri Lab

Postdoctoral Research Associate - Yttri Lab

Carnegie Mellon University

Pittsburgh, PA • On-site

Full-time

Posted 20 days ago

Carnegie Mellon University rating

8.6

Company rating: 8.6 out of 10

Based on 24 frontline employees who took The Breakroom Quiz

56th of 553 rated colleges and universities

Job description

Description
The Yttri lab at Carnegie Mellon University is looking for a talented postdoctoral associate to interrogate the circuit dynamics underlying naturalistic behavior. Building off our unsupervised algorithm for segmenting behaviors from video (Hsu and Yttri, Nature Communications), we are looking to explore the interactions between multiple brain areas over long time scales (weeks) as mice navigate their arena and/or learn new tasks. Several avenues are open to research, including interrogation of timescales of representation, plasticity, and circuit dynamics in normal mice and disease models. Eric and the lab are committed to building a supportive community for inquiry and curiosity that foster members to become better scientists and people.
Qualifications
PhD or MD, background in neuroscience or statistical methods. Background in population-level analysis of neural data and/or basic machine learning principles required, but needn't have been applied to rodent studies.
Application Instructions
Applications, including a cover letter and a curriculum vitae indicating your interest and relevant training should be submitted electronically via Interfolio.

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