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Postdoctoral In Bayesian Statistics Jobs in Michigan

Varsity Tutors

Statistics Graduate Level Tutor

Detroit, MI · 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 ...

University of Michigan

RESEARCH FELLOW

Ann Arbor, MI · On-site

Job Summary Postdoctoral Fellow in Statistical Genetics and Regulatory Genomics The Parker Lab at the University of Michigan ( is recruiting a Postdoctoral Fellow to lead statistical genetics ...

Epitec

Data Scientist

Southfield, MI · On-site

$128K/yr

... in Python, ensuring seamless integration with diverse data ecosystems while adhering to best ... statistical methodologies including Regression Analysis, Bayesian Inference, and machine learning ...

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Postdoctoral In Bayesian Statistics information

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.
What are popular job titles related to Postdoctoral In Bayesian Statistics jobs in Michigan? For Postdoctoral In Bayesian Statistics jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Postdoctoral In Bayesian Statistics jobs in Michigan look for? The top searched job categories for Postdoctoral In Bayesian Statistics jobs in Michigan are:
Postdoctoral In Bayesian Statistics jobs near you
Infographic showing various Postdoctoral In Bayesian Statistics job openings in Michigan as of June 2026, with employment types broken down into 29% Locum Tenens, 14% Internship, 14% Full Time, and 43% Nights. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution.
Department of Statistics RESEARCH FELLOW

Department of Statistics RESEARCH FELLOW

University of Michigan

Ann Arbor, MI • On-site

$65K - $80K/yr

Full-time

Posted 21 days ago

University Of Michigan rating

8.1

Company rating: 8.1 out of 10

Based on 140 frontline employees who took The Breakroom Quiz

134th of 544 rated colleges and universities

Job description

How to Apply
To apply, please submit the following materials via email to: [email protected]
  • A cover letter summarizing research experience and interests
  • Curriculum vitae, including publications and/or preprints
  • Contact information for three references

Applications will be reviewed on a rolling basis until the position is filled.
Job Summary
The Terhorst Lab in the Department of Statistics at the University of Michigan is recruiting a postdoctoral research fellow in statistical genetics and computational genomics. The position is part of a collaborative project with the University of Edinburgh and the University of Oxford focused on developing scalable methods for complex trait analysis using ancestral recombination graphs (ARGs).
Research areas include statistical/quantitative/population genetics, genealogical inference, machine learning, genetic prediction, genome-wide association studies, scalable linear mixed models, and efficient algorithms for large-scale genomic data analysis.
This is a one-year appointment starting as early as possible, with renewal possible based on the availability of funds, availability of work, and satisfactory performance.
Responsibilities*
  • Develop novel statistical and computational methods for ARG-based quantitative genetics
  • Analyze large-scale genetic and phenotypic datasets
  • Implement scalable software and algorithms for genomic inference
  • Collaborate with researchers across statistics, genetics, and computational biology
  • Contribute to manuscripts, presentations, and open-source software development
  • Participate in interdisciplinary collaborations related to predictive breeding and genome editing
  • Travel to the United Kingdom to collaborate with project partners at the University of Edinburgh and the University of Oxford

Required Qualifications*
  • PhD in statistics, computer science, computational biology, genetics, applied mathematics, or a related quantitative field is required
  • Proof of degree completion must be in hand on or before the start date
  • Strong programming and computational skills
  • Experience with statistical modeling, machine learning, or large-scale data analysis

Desired Qualifications*
  • Experience with population genetics or statistical genetics
  • Familiarity with Bayesian methods, probabilistic modeling, or graphical models
  • Experience with scientific computing in Python, JAX, Torch, Julia, C++, or related languages
  • Experience with high-performance computing or scalable algorithms
  • Interest in interdisciplinary research spanning genomics and evolutionary biology

Modes of Work
The position is on-site in Ann Arbor, Michigan.
Additional Information
Salary and Benefits: Salary will be commensurate with experience and is expected to be in the range of $65,000 - $80,000 per year, plus benefits and a $3,000 relocation assistance bonus.
Background Screening
The University of Michigan conducts background checks on all job candidates upon acceptance of a contingent offer and may use a third-party administrator to conduct background checks. Background checks are performed in compliance with the Fair Credit Reporting Act.
Contact Information
Please direct questions about the position to Jonathan Terhorst at [email protected] .
Please direct questions about how to apply to: [email protected]
U-M EEO Statement
The University of Michigan is an Equal Opportunity Employer. We are committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants, including protected veterans and individuals with disabilities.
Job Detail
Job Opening ID
277543
Working Title
Department of Statistics RESEARCH FELLOW
Job Title
RESEARCH FELLOW
Work Location
Ann Arbor Campus
Ann Arbor, MI
Modes of Work
Onsite
Full/Part Time
Full-Time
Regular/Temporary
Regular
FLSA Status
Exempt
Organizational Group
College Of Lsa
Department
LSA Statistics
Posting Begin/End Date
5/12/2026 - 7/11/2026
Salary
$65,000.00 - $80,000.00
Career Interest
Research Fellows

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The University of Michigan (U-M), based in Ann Arbor, MI, US, is one of America's most esteemed institutions in higher education. Established in 1817, it presides in the industry of education and research, providing a range of services including undergraduate, graduate, and professional education programs. Complementing this is an extensive research activity that has significantly contributed to various fields, from healthcare to engineering, humanities to sports. Upholding its mission "to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values", U-M consistently ranks among the top universities globally, a testament to its tradition of excellence in learning and research, and a deep commitment to innovation and discovery.

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