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Bayesian Research Jobs (NOW HIRING)

The Urbut Lab has a unique research fellow position open for a highly qualified applicant interested in dynamic modeling using multimodal data and causal inference for Bayesian analysis of EHR across ...

Postdoctoral Research Associate - Statistical Methods for Pediatric Oncology Clinical Trials ... Bayesian statistics * Causal inference * External controls or real-world evidence * Target trial ...

Senior Research Scientist

Boston, MA · On-site

$110K - $155K/yr

We are seeking a Senior Research Scientist to lead hypothesis‑driven research that translates ... methods, Bayesian inference, and/or causal inference. * Ability to work across disciplines and ...

Premier Research is looking for a Statistical Scientist Director to join our Biostatistics team ... Develops sample size estimation, modeling approaches, adaptive or Bayesian frameworks, and ...

S. farms, and we seek a Research Soil Scientist to support this mission for potato cropping systems ... Deploy and modify existing empirical models (currently multivariate and Bayesian) build with ...

Careers / Quant Research Engineer, Derived Data Products We are looking for a Quant Research ... Familiarity with smoothing filters, microstructure noise models, interpolation schemes, Bayesian ...

$100 - $125/hr

S. farms, and we seek a Research Soil Scientist to support this mission for potato cropping systems ... Deploy and modify existing empirical models (currently multivariate and Bayesian) build with ...

Experience with both Bayesian and frequentist statistical methods Nice to Haves * Published applied research or technical writing * Experience in consulting or customer-facing technical roles

Research Scientist

Baltimore, MD · Remote

$120K - $150K/yr

Familiarity with uncertainty quantification methods (e.g., ensembles, Bayesian inference) and ... Participate in regular team research reviews, contributing to and receiving feedback on methods and ...

Showing results 41-60

Bayesian Research information

What is Bayesian research?

Bayesian research refers to the use of Bayesian statistics and probability theory to analyze data, build predictive models, and support decision-making. Unlike traditional (frequentist) methods, Bayesian approaches incorporate prior knowledge or beliefs, updating them as new evidence becomes available. This makes Bayesian research particularly useful in fields where data is limited or uncertain, and it allows for more flexible and interpretable models. Bayesian research is widely used in fields like machine learning, medicine, economics, and social sciences.

What types of projects do Bayesian researchers typically work on?

Professionals in Bayesian Research often engage in projects involving statistical modeling, data analysis, and the development of probabilistic algorithms for applications such as machine learning, healthcare analytics, finance, and engineering. The work environment is highly collaborative, frequently requiring interaction with data scientists, domain experts, and software engineers to translate theoretical models into practical solutions. Team members regularly participate in interdisciplinary meetings to discuss model assumptions, share findings, and iterate on research approaches, making strong communication skills essential for success in this role.

What are the key skills and qualifications needed to thrive as a Bayesian researcher?

To thrive as a Bayesian Researcher, you need a strong background in statistics, probability theory, and data analysis, usually supported by an advanced degree in statistics, mathematics, or a related field. Proficiency with programming languages such as R or Python, statistical software (e.g., Stan or BUGS), and knowledge of Bayesian modeling techniques is essential. Strong problem-solving skills, critical thinking, and effective communication help you interpret results and collaborate with interdisciplinary teams. These competencies ensure rigorous, reliable research outcomes and enable impactful contributions to scientific or business decision-making.

What is the difference between Bayesian Research vs Data Scientist?

AspectBayesian ResearchData Scientist
Required CredentialsAdvanced degrees in statistics, mathematics, or related fields; knowledge of Bayesian methodsDegree in computer science, statistics, or related fields; programming skills
Work EnvironmentResearch-focused, often in academia or specialized industriesBusiness or tech environments, applying data analysis to solve practical problems
Industry UsageUsed in research, academia, and industries requiring probabilistic modelingApplied across various industries including tech, finance, healthcare

Bayesian Research primarily focuses on developing and applying Bayesian statistical methods for research purposes, often in academic or specialized settings. Data Scientists utilize a broader set of data analysis tools, including Bayesian techniques, to interpret data and inform business decisions across diverse industries.

What other helpful pages are available for Bayesian Research?

Other pages related to Bayesian Research:

Infographic showing various Bayesian Research job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 88% Full Time, 9% Part Time, and 1% Contract. Highlights an 79% Physical, 3% Hybrid, and 18% Remote job distribution.

Research Fellow

Boston, MA • On-site

Full-time

Posted 9 days ago


Brigham and Women's Hospital rating

8.1

Company rating: 8.1 out of 10

Based on 101 frontline employees who took The Breakroom Quiz


Job description

Site: The General Hospital Corporation
Mass General Brigham relies on a wide range of professionals, including doctors, nurses, business people, tech experts, researchers, and systems analysts to advance our mission. As a not-for-profit, we support patient care, research, teaching, and community service, striving to provide exceptional care. We believe that high-performing teams drive groundbreaking medical discoveries and invite all applicants to join us and experience what it means to be part of Mass General Brigham.
Job Summary
APPLY BY EMAIL ONLY - APPLICATION INSTRUCTIONS BELOW
The laboratory of Dr. Sarah Urbut is located within Mass General Brigham's Heart and Vascular Institute's (MGB HVI) Cardiovascular Research Center (CVRC) and also is affiliated with the Broad Institute of Harvard & MIT and Harvard Medical School. Dr. Urbut leads cutting-edge research in principled method development to integrate electronic health records (EHR) with genetics for both prediction and discovery.
The Urbut Lab has a unique research fellow position open for a highly qualified applicant interested in dynamic modeling using multimodal data and causal inference for Bayesian analysis of EHR across cohorts, hospital-based biobanks, and within clinical trials. The new hire will be appointed as a Research Fellow at the Massachusetts General Hospital and at Harvard Medical School.
This position will leverage stimulating environments and resources across world-class institutions. Individuals will work with a range of genetic datasets, including genome-wide arrays, whole exome sequencing, and whole genome sequencing, as well as multi-omics data (e.g., metabolic, transcriptomic, proteomic, methylation). The successful candidate(s) will join an interdisciplinary team of computational biologists, bioinformatics analysts, epidemiologists, physicians, nurses, clinical research coordinators, and students.
Please visit surbut.github.io/Urbut_lab (in process) for additional details about prior, ongoing, and future research. The high prevalence of cardiovascular disease, the leading cause of premature death worldwide, coupled with increasingly massive patient and genetic data, has motivated the Urbut Lab to pursue highly innovative research studies to guide future therapeutic development and diagnostic tools.
The successful candidate will work closely with members of the Urbut Lab as well as Dr. Urbut directly. The successful candidate will be closely supervised by Dr. Urbut. The successful candidate will have robust facility in computational genetics and biostatistics. Projects will range from genomic discovery and in silico investigations of genetic mechanisms of disease risk prediction, digital twin development, and genomic discovery through multi-feature hypothesis-generating studies with multi-omics, imaging, and electronic health records.
Overall, this is a unique opportunity to engage in cutting-edge science and make a central contribution to biomedical research. In addition, Mass General Brigham, Massachusetts General Hospital, and the Broad Institute provide vibrant research environments with close links to top academic and industry networks across the Greater Boston area and the world.
Key Responsibilities
• Construction and implementation of cloud-based pipelines for genomic, polygenic risk scoring, and biostatistical analyses.
• Processing and quality control of next-generation sequence data.
• Processing and quality control of multi-omics data.
• Statistical analyses of genotype-phenotype association analyses, with summarization and graphical representations.
• Organizing, manipulating, and harmonizing new datasets across different formats and robust synchronization with existing datasets and databases.
• Phenotypic derivation from electronic health record structured and unstructured data.
• Construction, implementation, and sensitivity analyses of biostatistical models in classical epidemiology, genetic epidemiology, and machine learning.
• Lead and contribute to manuscript preparation as well as internal and external project-team reports.
• Actively participate and present in project meetings.
Work will be performed in the Simches Research Building on the Massachusetts General Hospital main campus, in Boston, MA.
Qualifications
The ideal candidate should have received (or expect to receive soon) a doctoral degree. A doctoral degree will be required to complete onboarding.
  • First (or co-first) author of one or more peer-reviewed scientific publications
  • Excellent English verbal and written communication skills
  • Able to work both independently and in a team
  • Doctoral degree in computational biology, biomedical informatics, biostatistics, statistical genetics, genetic epidemiology, or computer science.
  • Strong record of productivity, motivation, adaptability, and collaboration.
  • Exceptional oral and written communication skills.
  • Strong background in computational biology and bioinformatics.
  • Strong skills in statistical analyses are highly preferred.
  • Strong demonstrable proficiency in Linus, R, python and AWS use.
  • Strong facility with cloud computing.
  • Prior experience in human genetic analyses and bioinformatics analyses of publicly available datasets.
  • Familiarity with next-generation sequence data analysis tools strongly preferred.
  • Ability to adapt to rapidly changing and high-demand environments.
  • Knowledge of cardiovascular disease is not required.

The salary for this position ranges from $73,544-$81,179.
Additional Job Details (if applicable)
IMPORTANT - APPLICATION INSTRUCTIONS
Please do not apply through the Workday "Apply" button.
This position is being posted for informational purposes only. To be considered, please submit the following directly to the hiring manager by clicking the link below:
  • CV/resume
  • Cover letter

📧 [Click Here to Email Your Application]
Please note: Applications submitted through Workday will not be forwarded to the hiring manager and may not be reviewed.
Remote Type
Onsite
Work Location
185 Cambridge Street
EEO Statement:
1200 The General Hospital Corporation is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religious creed, national origin, sex, age, gender identity, disability, sexual orientation, military service, genetic information, and/or other status protected under law. We will ensure that all individuals with a disability are provided a reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. To ensure reasonable accommodation for individuals protected by Section 503 of the Rehabilitation Act of 1973, the Vietnam Veteran's Readjustment Act of 1974, and Title I of the Americans with Disabilities Act of 1990, applicants who require accommodation in the job application process may contact Human Resources at (857)-282-7642.
Mass General Brigham Competency Framework
At Mass General Brigham, our competency framework defines what effective leadership "looks like" by specifying which behaviors are most critical for successful performance at each job level. The framework is comprised of ten competencies (half People-Focused, half Performance-Focused) and are defined by observable and measurable skills and behaviors that contribute to workplace effectiveness and career success. These competencies are used to evaluate performance, make hiring decisions, identify development needs, mobilize employees across our system, and establish a strong talent pipeline.

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