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Postdoctoral In Bayesian Statistics Jobs in Michigan

Bachelors degree in mathematics, statistics, physics, pharmacology or with a strong statistical ... Experience of Bayesian approaches to design and analysis of clinical data preferred. * Experience ...

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 ...

... Postdoc / Junior professor) to participate in a high-impact project supporting a customer in the ... Statistical Physics, Condensed Matter, AMO/Quantum Optics, Gravitation/Cosmology, Quantum ...

... Postdoc / Junior professor) to participate in a high-impact project supporting a customer in the ... Statistical Physics, Condensed Matter, AMO/Quantum Optics, Gravitation/Cosmology, Quantum ...

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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 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 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:

Infographic showing various Postdoctoral In Bayesian Statistics job openings in Michigan 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.

Postdoctoral Research Fellow

Ann Arbor, MI • On-site

Other

Posted 13 days ago


Job description

University of Michigan Department of Biostatistics – Postdoctoral Research Fellow Company Name University of Michigan Department of Biostatistics Position Title Postdoctoral Research Fellow Company Information

The Department of Biostatistics is ranked No. 3 nationally by U.S. News & World Report. We are a thriving community of 47 faculty members, 16 postdoctoral fellows, 243 students, and 124 research and administrative staff, with strong ties to the Department of Statistics, the Medical School, the Michigan Institute for Data Science, and other research groups across the University of Michigan.

Duties and Responsibilities

The Department of Biostatistics at the University of Michigan School of Public Health invites applications for a postdoctoral fellow position in the broad areas of statistics, data science, and artificial intelligence (AI). The position will focus on developing and applying novel statistical, machine-learning, and AI methods to advance biomedical and oncology research.

The fellow will work under the supervision of Yi Li, with opportunities to collaborate with faculty in the Department of Biostatistics as well as medical and biomedical investigators at the University of Michigan and Harvard University. The position is funded by several NIH grants.

The start date is flexible; the selected candidate will ideally begin as soon as possible.

The postdoctoral fellow will work with Dr. Yi Li and his research group to develop innovative statistical and computational methods for large-scale, high-dimensional, and complex biomedical data. Research topics include but are not limited to modern survival analysis, high-dimensional statistical inference, AI and machine learning, deep learning and its statistical foundations, causal inference, statistical methods for medical imaging, precision medicine, statistical genomics, graphical models, and the analysis and integration of complex, high-dimensional biomedical data.

The fellow will be expected to develop novel statistical methodology and apply it in real-world biomedical studies, prepare manuscripts for peer-reviewed journals, present and disseminate research findings, and collaborate with biomedical and clinical investigators.

There will also be opportunities to contribute to the teaching of graduate courses. The successful candidate will receive a competitive salary, computing resources, and other benefits in accordance with departmental and university policies.

The work requirements allow both onsite and offsite work and an employee has an expected recurring onsite presence. On occasion, the employee may be required and must be available to work onsite more frequently if necessitated by unit leadership or their designee and/or the job requirements.

This position may be eligible for remote and/or flexible work opportunities at the discretion of the hiring department. Flexible work agreements are reviewed annually and are subject to change based on the business needs of the hiring department throughout the course of employment.

Ann Arbor is a progressive city of approximately 118,000 year-round residents and approximately 43,000 students, with excellent schools and a wide variety of cultural, recreational, sporting, and musical activities. It consistently ranks highly in national surveys for quality of life and offers the amenities of a city many times its size.

In addition to a career filled with purpose and opportunity, the University of Michigan offers a comprehensive benefits package to help employees stay well, protect themselves and their families, and plan for a secure future.

This is a one-year appointment with the possibility of renewal for up to two additional years, contingent upon satisfactory performance and the availability of funding.

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.

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.

Position Qualifications
  • PhD in Biostatistics, Statistics, Mathematics, Computer Science, or a related quantitative field by the time of appointment
  • Strong methodological and computational skills
  • Demonstrated interest or experience in health-related applications of statistical, data science, machine-learning, or AI methods
  • Strong written and oral communication skills
  • Ability to work collaboratively in interdisciplinary research teams

Applicants should submit the following materials as a single document:

  1. A cover letter describing their specific interest in the position, relevant skills and experience, and overall research interests and plans (no more than 3 pages);
  2. A curriculum vitae;
  3. The names and contact information of three references.

Please submit application materials and any questions about the position to Yi Li at yili@umich.edu.

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