1

Postdoctoral In Bayesian Statistics Jobs in Houston, TX

Postdoctoral Fellow - Genetics

Houston, TX · On-site

$64K - $76K/yr

  • Medical

  • Dental

  • Retirement

  • PTO

The Yun Laboratory in the Department of Genetics at The University of Texas MD Anderson Cancer ... statistical skills when appropriate, and drive projects toward publication. We are particularly ...

Postdoctoral Fellow - Genetics

Houston, TX

$64K - $76K/yr

  • Medical

  • Dental

  • Retirement

  • PTO

The Yun Laboratory in the Department of Genetics at The University of Texas MD Anderson Cancer ... statistical skills when appropriate, and drive projects toward publication. We are particularly ...

Postdoctoral Fellow - Genetics

Houston, TX

$64K - $76K/yr

  • Medical

  • Dental

  • Retirement

  • PTO

The Yun Laboratory in the Department of Genetics at The University of Texas MD Anderson Cancer ... statistical skills when appropriate, and drive projects toward publication. We are particularly ...

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

Postdoctoral Fellow - Pharmacology

Galveston, TX · On-site

$46K - $62K/yr

The postdoctoral fellow will conduct, report and present research in his/her field of study under ... in research conferences and for manuscript preparation; use graphics and statistical software to ...

Showing results 41-60

Postdoctoral In Bayesian Statistics information

See Houston, TX salary details

$23.9K

$56.4K

$79.7K

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

As of Aug 15, 2026, the average yearly pay for postdoctoral in bayesian statistics in Houston, TX is $56,364.00, according to ZipRecruiter salary data. Most workers in this role earn between $46,800.00 and $63,500.00 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?

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 Houston, TX?

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

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

The top searched job categories for Postdoctoral In Bayesian Statistics jobs in Houston, TX are:

What cities near Houston, TX are hiring for Postdoctoral In Bayesian Statistics jobs?

Cities near Houston, TX with the most Postdoctoral In Bayesian Statistics job openings:

Infographic showing various Postdoctoral In Bayesian Statistics job openings in Houston, TX 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 $56,364 per year, or $27.1 per hour.

Postdoctoral Fellow - Radiation Oncology - Research

MD Anderson

Houston, TX

Full-time

Medical, Dental, Retirement, PTO

Re-posted 5 days ago


MD Anderson Cancer Center rating

8.4

Company rating: 8.4 out of 10

Based on 170 frontline employees who took The Breakroom Quiz

23rd of 887 rated healthcare providers


Job description

The Postdoctoral Fellow will serve as a technical research and data-engineering lead supporting large-scale, NIH-funded translational oncology studies, including the OPULENCE R01 program, which focuses on developing multimodal data standards and predictive models of oral and dental toxicities experienced by patients with head and neck cancers (HNC) who are treated with radiation therapy.
This role is best suited for a proactive individual who demonstrates strong analytical thinking skills necessary to tackle challenging data science problems and who enjoys finding innovative solutions towards building efficient data systems, pipelines, and standards. The postdoctoral fellow will design, implement, and maintain research-grade data infrastructure spanning clinical, imaging, patient-reported outcomes (PROs), dental/oral health, biospecimens, and derived AI/ML features, using both structured and unstructured data sources.
The position blends research operations, data engineering, and informatics, with opportunities to contribute to ontology development, LLM-enabled data extraction, and advanced analytics pipelines in collaboration with clinicians, dentists, physicists, informaticians, and data scientists. Moreover, this position provides opportunities for manuscript writing, grantsmanship, and advancement in associated research career trajectories.
All duties and responsibilities are carried out in compliance with institutional policies, ethical research standards, and applicable federal and state regulations.
LEARNING OBJECTIVES
Research Data Engineering & Systems Development
• Design, build, and maintain production-quality research data pipelines supporting prospective and retrospective oncology cohorts.
• Implement ETL / ELT workflows to ingest, transform, validate, and harmonize structured and unstructured data from:
• Electronic health records (EHR)
• Imaging metadata and derived features
• Patient-reported outcomes (ePROs)
• Dental and oral health assessments
• Research databases and external registries
• Proactively identify opportunities to improve data quality, completeness, and reproducibility across research workflows.
• Serve as a technical resource for data model design, schema evolution, and versioning.
Database, Ontology, and Standards Development
• Support the development and maintenance of research ontologies and common data elements (CDEs) aligned with national standards (e.g., clinical, imaging, and outcomes domains).
• Translate existing research data models into ontology-based representations to support analytics, interoperability, and AI workflows.
• Document data schemas, ontologies, transformations, and analytical assumptions to support transparency and reuse.
• Collaborate with investigators to refine data structures that improve extensibility, semantic clarity, and downstream analysis.
Advanced Analytics, AI/ML, and LLM Enablement
• Prepare structured and unstructured datasets for predictive, descriptive, and exploratory modeling, including AI/ML and statistical analyses.
• Support LLM-based workflows for extraction of clinical concepts from free-text (e.g., clinical notes, imaging reports, pathology reports).
• Assist with feature engineering, cohort construction, and data serialization for modeling and visualization platforms.
Platform & Tooling (Foundry Desired, Not Required)
• Build and manage data assets using modern analytics platforms; experience with Palantir Foundry is desired but not required.
• For Foundry users:
• Create and maintain backing datasets, transformations, and ontology objects
• Implement data validations, permissions, and pipeline monitoring
• Design and deploy interactive, ontology-driven workflow-specific Workshop Apps
• For non-Foundry users:
• Apply equivalent best practices using relational databases, Python/SQL workflows, and cloud or on-prem research environments.
Collaboration, Documentation, and Research Operations
• Work closely with clinicians, research coordinators, statisticians, and informatics teams to translate scientific questions into data solutions.
• Produce clear technical documentation (data dictionaries, pipeline descriptions, SOPs).
• Support IRB-compliant data governance, including secure handling of PHI and research data.
• Assist with onboarding and training of research staff in data systems and best practices.
• Contribute to abstracts, figures, and analytic summaries for publications and grant reporting
ELIGIBILITY REQUIREMENTS
The appointee recently (within three years) completed their education (doctorate) or completed previous postdoctoral experience or graduate medical education
The appointment is temporary
The appointment involves substantial full-time research or scholarship
The appointment is viewed as preparatory for a full-time academic and/or research career
The appointment is not part of a clinical training program
The appointee works under the supervision of a senior scholar or a department in a university or similar research institution (e.g., national laboratory, National Institutes of Health (NIH), etc.)
The appointee has the freedom to and is expected to publish the results of his or her research or scholarship during the period of the appointment
POSITION INFORMATION
MD Anderson offers full-time postdoc positions with a salary ranging from $64,000 to $76,000. depending on the number of years of postgraduate experience. The University of Texas MD Anderson Cancer Center offers excellent benefits, including medical, dental, paid time off, retirement, tuition benefits, educational opportunities, and individual and team recognition
Offsite work arrangements are subject to approval and may be modified or revoked at any time based on business needs, performance considerations, or regulatory requirements.
This position may be responsible for maintaining the security and integrity of critical infrastructure, as defined in Section 113.001(2) of the Texas Business and Commerce Code and therefore may require routine reviews and screening. The ability to satisfy and maintain all requirements necessary to ensure the continued security and integrity of such infrastructure is a condition of hire and continued employment.
It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state or local laws unless such distinction is required by law. http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html

What MD Anderson Cancer Center employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom