Student Worker

Job description

We are seeking a motivated undergraduate student to join our cancer epidemiology research team. This position offers hands-on experience in public health research, with a focus on analyzing and harmonizing data from multiple studies related to ovarian cancer outcomes, risk factors, and survivorship. The candidate will work under the supervision of Dr. Shelley S. Tworoger to support research projects related to ovarian cancer etiology, outcomes, and risk factors. The candidate will focus on data analysis and harmonization of data from multiple studies.
Duties Include:
• Assist with cleaning, organizing, and harmonizing epidemiologic datasets from diverse sources.
• Conduct descriptive and inferential statistical analyses using software such as R, SAS, or Python.
• Support literature reviews and data documentation efforts.
• Collaborate with team members to ensure data quality and consistency across studies.
• Develop graphs and tables for use by investigators and for publication, grants, and presentation.
• Potential for co-authorship on scientific publications or presentations.
• Participate in regular laboratory meetings and contribute to discussions on data interpretation and research findings.
• Acquire advanced skills for analyzing complex epidemiological data, including high-throughput data.
• Develop advanced proficiency in programming and bioinformatics.
• Receive guidance on career planning and job search strategies.

Enrolled in or on vacation from or is otherwise registered in:
• High School, OR
• Undergraduate Program (minimum 6 credit hours), OR
• Graduate Program minimum 4.5 credit hours)
• Current undergraduate student in public health, epidemiology, biostatistics, data science, or a related field.
• Basic knowledge of statistical software (e.g., R, SAS, SPSS, or Python).
• Strong attention to detail and organizational skills.
• Interest in cancer research and population health.
• Ability to work independently and as part of a collaborative team.
• Experience with data cleaning and management.
• Familiarity with epidemiologic study designs and variables.
• Prior coursework in statistics or epidemiology.