Assistant Professor, Division of Biostatistics & Epidemiology - JR225309

Cwstat

Cincinnati (OH)

On-site

USD 90,000 - 130,000

Full time

2 days ago
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Job summary

Cincinnati Children’s Division of Biostatistics & Epidemiology seeks an Assistant Professor to lead innovative statistical research and apply AI methods to health data. You will collaborate with clinical and informatics teams, mentor trainees, and pursue external funding in pediatric biostatistics.

The role emphasizes building a fundable research program, publishing work, and advancing methods applicable to child health outcomes.

Qualifications

  • PhD in statistics/biostatistics with a health research focus.
  • Experience developing fundable research programs and publishing peer‑reviewed work.
  • Interest in integrating AI into medical and health research.

Responsibilities

  • Develop and lead a robust research program in statistical methodology development.
  • Develop and apply AI methodologies to enhance biomedical and population health research.
  • Establish strong collaboration with other divisions or investigators.
  • Provide mentorship to postdoctoral fellows, students and staff, enriching the academic and research environment.
  • Effectively manage research funding and contribute to the division's resource development.

Skills

Statistical methods
AI in health research
Mentorship
Grant writing

Education

PhD in statistics/biostatistics

Job description

This is a current listing of job announcements related to Statistics.To submit a job for posting please use the Statistics Job Submission Form . Please note that jobs are posted within 24hrs of submission. If you have any questions, comments, or need to make acorrectionregarding your job announcement, please contact jobs@stat.ufl.edu .

Cincinnati Children's – Assistant Professor, Division of Biostatistics & Epidemiology – JR225309
Position Title Assistant Professor, Division of Biostatistics & Epidemiology - JR225309
Company Information

About the Division: The Division of Biostatistics and Epidemiology at Cincinnati Children's Research Foundation includes twenty faculty and more than fifty staff with expertise in numerous statistical and epidemiological methods that advance understanding of child health. The Division partners with nearly all of the clinical and translational research programs of Cincinnati Children's, including established and emerging collaborations with the Division of Biomedical Informatics for projects requiring cutting-edge, high-dimensional data analysis techniques. Our faculty conduct independently funded research to develop statistical methods and advance the field of pediatric epidemiology. In addition to conducting research, the Division operates a shared research facility, the Data Management and Analysis Collaborative (DMAC)(https://www.cincinnatichildrens.org/research/shared-facilities/data-management-analysis), which leverages the statistical and epidemiological expertise of our faculty and staff to expand its ability to support the research enterprise of Cincinnati Children's. It is the largest centralized resource for study design, data management, and statistical analysis solely housed within the organization.

Duties and Responsibilities

Key Responsibilities:

  • Develop and lead a robust research program in statistical methodology development.
  • Develop and apply AI methodologies to enhance biomedical and population health research.
  • Establish strong collaboration with other divisions or investigators.
  • Provide mentorship to postdoctoral fellows, students and staff, enriching the academic and research environment.
  • Effectively manage research funding and contribute to the division's resource development.
Position Qualifications

Qualifications:

  • Ph.D. in statistics, biostatistics, or related discipline, with demonstrated experience in health research.
  • Demonstrated potential to develop a fundable research program, supported by significant contributions to peer-reviewed literature and the aptitude to compete successfully for external research funding.
  • Demonstrated mentorship and research training experience.
  • Interest in integrating AI into medical and health research.
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