Texas A&M University Health Sciences Center
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Postdoctoral Research Associate in Health Policy, Health Informatics, and Data Science Texas A&M University Health Science Center in United States
Degree Level
Postdoc
Field of study
Computer Science
Funding
Grant-funded postdoctoral position; future employment may depend on future funding. Salary is commensurate.
Country
United States
University
Texas A&M University Health Sciences Center

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About this position
Texas A&M University Health Science Center is advertising a Postdoctoral Research Associate position in the Department of Health Policy and Management at College Station, Texas, United States.
The role is based in the Population Informatics Lab and focuses on research in health policy, health informatics, public health, biostatistics, data science, and related areas. The postdoctoral researcher will design health database studies, manage and analyze data, write reports and papers, and contribute to publications. The position also includes mentoring student researchers and helping prepare technical progress reports and presentations.
Eligibility highlights: applicants should have an appropriate PhD in Information Science or a related field. Preferred experience includes statistical programming and machine learning with tools such as R, Python, SAS, or STATA; work with large population datasets such as EHR or claims data; and background in health informatics, population health research, biostatistics, or computer science. Experience in grant writing, qualitative research, survey research, and mixed methods is a plus.
Funding: this is a grant-funded postdoctoral appointment, and continued employment may depend on future funding. Salary is commensurate.
Application: applicants should apply through the Workday portal using the provided link. A cover letter and resume are strongly recommended. The posting does not list a deadline.
Funding details
Grant-funded postdoctoral position; future employment may depend on future funding. Salary is commensurate.
What's required
Appropriate PhD in Information Science or a related field. Preferred background includes a PhD in data science, public health, health services research, health informatics, computer science, or related fields. Experience with data analysis using statistical software and machine learning tools such as R, Python, SAS, or STATA is preferred, along with experience working with large population datasets such as EHR or claims data. Additional desirable experience includes health informatics, population health research, biostatistics, grant writing, qualitative research, survey research, and mixed methods.
How to apply
Apply through the Workday application portal using the provided job link. A cover letter and resume are strongly recommended, and applicants should ensure all application data is complete or upload a resume to avoid rejection.
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