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Postdoctoral In Bayesian Statistics Jobs (NOW HIRING)

ChromoLogic

Senior Scientist, Bioinformatics

Monrovia, CA · On-site

$90K - $120K/yr

Apply advanced machine learning, Bayesian statistics, and predictive modeling techniques to ... D. in Computational Biology, Bioinformatics, Biostatistics, Statistics, Computer Science, or a ...

Statistics Interest Group

... survival analysis, Bayesian methods, analysis of social and biological network data, systems ... The Department offers a highly regarded PhD program in Statistics; it also runs two master's degree ...

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

As of Sep 14, 2026, the average yearly pay for postdoctoral in bayesian statistics in the United States is $59,022.00, according to ZipRecruiter salary data. Most workers in this role earn between $49,000.00 and $66,500.00 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 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.

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Infographic showing various Postdoctoral In Bayesian Statistics job openings in the United States as of September 2026, with employment types broken down into 2% Internship, 79% Full Time, 18% Part Time, and 1% Contract. Highlights an 78% Physical, 4% Hybrid, and 18% Remote job distribution, with an average salary of $59,022 per year, or $28.4 per hour.

Senior Scientist, Bioinformatics

Monrovia, CA • On-site

ChromoLogic
Retail • 11 - 50 employees
Learn more about ChromoLogicexternal

Other

Re-posted 22 days ago

Job description

Drive the Future of Precision Medicine

ChromoLogic is advancing transformative biomedical technologies through cutting-edge research and development programs focused on nucleic acid biomarkers and next-generation diagnostics. We are seeking an innovative and highly motivated Senior Scientist, Bioinformatics to lead the discovery, development, and validation of novel biomarkers for prognostic and precision medicine applications.

This role offers an opportunity to work at the forefront of genomics, machine learning, and translational research. The successful candidate will collaborate closely with multidisciplinary teams of scientists, data analysts, and external partners to transform complex biological data into actionable insights that improve patient outcomes.

ChromoLogic LLC (www.chromologic.com) is a world-class innovation center with advanced scientific research and development in the medical, aerospace and security markets.

What You'll Do Scientific Leadership & Innovation
  • Lead bioinformatics efforts supporting the discovery and validation of nucleic acid biomarkers
  • Develop, optimize, and maintain robust computational pipelines for NGS and multi-omics data analysis
  • Apply advanced machine learning, Bayesian statistics, and predictive modeling techniques to identify biologically meaningful patterns and biomarkers
  • Design and execute end-to-end analytical strategies, from hypothesis generation and experimental planning through data interpretation and reporting
Cross-Functional Collaboration
  • Partner with molecular biologists, experimental scientists, clinicians, and external collaborators to drive research programs forward
  • Translate complex computational results into clear scientific recommendations and business-relevant insights
  • Contribute to strategic planning and research initiatives across the organization's portfolio
Research Excellence
  • Evaluate emerging bioinformatics methodologies, tools, and technologies to enhance analytical capabilities
  • Ensure scientific rigor, reproducibility, and quality across all computational workflows
  • Author technical reports, peer-reviewed publications, research proposals, standard operating procedures (SOPs), and grant applications
  • Present findings to scientific teams, leadership, collaborators, and industry stakeholders
Required Qualifications
  • Ph.D. in Computational Biology, Bioinformatics, Biostatistics, Statistics, Computer Science, or a related quantitative discipline
  • 2-5+ years of postdoctoral, academic, biotechnology, pharmaceutical, or industry experience
  • Demonstrated expertise in next-generation sequencing (NGS) data analysis and bioinformatics workflow development
  • Strong proficiency in Python, R, or similar programming languages
  • Experience applying machine learning, Bayesian modeling, or advanced statistical methods to biological datasets
  • Proven ability to independently design studies, analyze complex datasets, and derive meaningful scientific conclusions
  • Strong record of collaboration in multidisciplinary research environments
  • Outstanding written, verbal, and presentation communication skills
Why Join Us?
  • Work on mission-critical technologies with real-world impact
  • Collaborate with top-tier scientists and engineers
  • Engage in meaningful, application-driven innovation
What We Offer
  • Competitive salary and benefits package
  • A mission-driven culture where discovery and innovation are at the heart of everything
  • Close collaboration with scientists and leaders shaping breakthrough research
  • A chance to build something meaningful-your systems, your ideas, your leadership
  • Flexible environment, high ownership, and the ability to make an immediate impact

If you're passionate about leveraging computational biology, machine learning, and genomics to solve complex biomedical challenges, we'd love to hear from you.

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