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Postdoctoral In Bayesian Statistics Jobs in Missouri

Post Doctoral Fellow

Columbia, MO · On-site

$46K - $63K/yr

The Postdoctoral fellow will advance cropping systems research at the University of Missouri Plant ... It is beneficial to have experience in several of the following areas: data processing, statistical ...

Position Summary We are considering the applications of a postdoctoral research fellow in neuroimaging, artificial intelligence (AI), and statistical genomics. This exciting career-building position ...

Information on being a postdoc at Washington University in St. Louis can be found at Lab website ... Statistical Genomics or a related discipline involving the interrogation of 'omics' datasets.

Postdoctoral Fellow

Saint Louis, MO · On-site

$47K - $64K/yr

The postdoctoral fellow at the Department of Internal Medicine at Saint Louis University School of ... Proficiency in statistical analysis software such as Stata, R, or SAS. * Strong interpersonal and ...

Postdoctoral Fellow

Saint Louis, MO · On-site

$47K - $64K/yr

The postdoctoral fellow at the Department of Internal Medicine at Saint Louis University School of ... Proficiency in statistical analysis software such as Stata, R, or SAS. * Strong interpersonal and ...

$45K - $62K/yr

Fellows gain advanced applied experience in public health research, statistical analyses and ... Information on being a postdoc at WashU in St. Louis can be found at Trains under the supervision ...

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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.
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Infographic showing various Postdoctoral In Bayesian Statistics job openings in Missouri as of July 2026, with employment types broken down into 83% Full Time, and 17% Part Time. Highlights an 84% In-person, 8% Hybrid, and 8% Remote job distribution.
Post Doctoral Fellow

Post Doctoral Fellow

University of Missouri

Columbia, MO • On-site

$46K - $63K/yr

Full-time

Medical, Dental, Vision, Retirement

Re-posted 11 days ago


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Job description

Job Description
The Postdoctoral fellow will advance cropping systems research at the University of Missouri Plant Science Department in collaboration with the USDA ARS Cropping Systems and Water Quality Research Unit. This is a two-year position focused on advancing crop production and physiology through field experimentation, computation (statistics and machine learning), and process-based models. The successful candidate will have an inquisitive nature with a deep knowledge of many components listed in this posting and a strong desire for continual learning and growth professionally. We invite candidates to submit an application if able to start in the next three months and are excited to work at the intersection of genotype x environment x management.
Responsibilities:
The fellow will work to identify crop and system-based strategies that advance knowledge and discovery to minimize stress and maximize economic and environmental health. Specifically, this will be achieved through use of data from the past 5 years and on-going across several Missouri experiments. Research topics include: 1) productivity and economics of intensified crop rotations, 2) management decisions based on crop phenology, 3) physiological and growth response to late-season stressors, and 4) plausibility of double-crop systems. The fellow is expected to write four papers, with three accepted and one submitted, during these two years. In addition to publishing in refereed journals, the fellow will develop lay materials to transfer key findings to farmers and agribusiness.
Qualifications
Minimum Qualification:
PhD, by time of appointment. Candidates need to have a PhD in agronomy, agroecology, ecology, soil science, natural resources, environmental science, agricultural engineering, statistics, data science, or similar discipline.
Candidates will be evaluated on:
Candidates need to have excellent written and oral communication skills in English. They must be able to work effectively independently, in teams, and across disciplines.
Candidates must have an excellent understanding of the processes underlying plant, soil, and environment within an agricultural setting.
Candidates must have a strong command of data synthesis, modeling, and/or machine learning. It is beneficial to have experience in several of the following areas: data processing, statistical analyses, R software, regression models, process-based models such as DSSAT or APSIM, Bayesian statistical analysis, geospatial data, and machine learning methods. No candidate is expected to have proficiency in all of these computer-based skills. Rather, the ideal candidate will be a well-rounded individual with a high aptitude to learn during the fellowship.
Application Materials
Apply online at https://hr.missouri.edu/job-openings , Job ID# 59893.
To apply, submit a single PDF file that includes 1) a letter of interest describing how your skills and interests make you a strong candidate for this position; 2) a current CV; and 3) contact information for three professional references.
Closing Date:
Applications will be received until midnight (CST) June 30, 2026. However, review of applications will begin 15 days after the job was posted.
Contact:
Reach out with questions about this postdoctoral fellowship to Dr. Andre Froes de Borja Reis, Assistant Professor and State Extension Specialist in Soybean Agronomy, areis@missouri.edu or 573-882-4771.
Sponsorship Information
Visa Sponsorship Information:
Applicants must be authorized to work in the United States. The University will not sponsor applicants for this position for employment visas.
Benefit Eligibility
This position is eligible for University benefits. As part of your total compensation, the University offers a comprehensive benefits package, including medical, dental and vision plans, retirement, and educational fee discounts for all four UM System campuses. For additional information on University benefits, please visit the Faculty & Staff Benefits website at https://www.umsystem.edu/totalrewards/benefits .
Equal Employment Opportunity
The University of Missouri is an Equal Opportunity Employer .
To request ADA accommodations, please call the Director of Accessibility and ADA at 573-884-7278.

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The University of Missouri, based in Columbia, MO, US; is a public, land-grant research institution with an established reputation in academic excellence, industry relevance, and societal impact. Founded in 1839, it was the first public university located west of the Mississippi River. The institution spans various industries in the education sector with its multitude of undergraduate, graduate, and professional degree programs across various disciplines. The University's mission is centered on improving lives, enhancing communities, advancing health, and fostering excellence through its teaching, research, and engagement activities. U-M has some significant achievements under its belt including pioneering the world's first school of journalism and being one of the only six public universities in the US that accommodates medicine, veterinary medicine, and law in one campus.

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