Graduate Student Assistant (Office) at San Diego State University Research Foundation
San Diego, CA 92182, USA -
Full Time


Start Date

Immediate

Expiry Date

08 Oct, 25

Salary

23.0

Posted On

08 Jul, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Completion, Spss, Communication Skills, Epidemiology, Sas, Public Health, Statistics, Psychology

Industry

Information Technology/IT

Description

THE SALARY FOR THIS POSITION IS $23.00 PER HOUR, 20 HOURS PER WEEK.

The Loss of Independence Study research team at SDSU involves a graduate student providing research assistance on data management and analysis of the National Health and Aging Trend Study (NHATS) assessing the factors contributing to loss of independence among multiethnic populations in the U.S. The research assistant will support data setup, data management, analyses, and disseminations.
We are seeking a Graduate Research Assistant with strong data analysis skills to support research projects in public health. The position will primarily focus on statistical data analysis, data management, and assisting with research-related tasks. This is an excellent opportunity for a graduate student to gain hands-on experience working with real-world datasets and contribute to meaningful research.
Responsibilities:

KNOWLEDGE & ABILITIES

  • Strong experience with statistical analysis software (SAS, SPSS, or similar).
  • Excellent attention to detail and organizational skills.
  • Strong verbal and written communication skills.

MINIMUM EDUCATION & EXPERIENCE

  • Equivalent to completion of a bachelor’s degree and registration in an SDSU graduate degree program.

PREFERRED QUALIFICATIONS & SPECIAL SKILLS

  • Currently enrolled in a graduate program (Master’s or PhD) in Public Health, Psychology, Statistics, Epidemiology, or a related field.
  • Experience working with large datasets.
  • Familiarity with epidemiological or social science research methods.
  • Knowledge of advanced statistical techniques (e.g., regression, mixed modeling).
Responsibilities

Qualifications:

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