Health Science Summer Research Assistant

Exact schedule to be determined with supervisor; no more than 20 hours per week when school is in session and no more than 35 hours per week during breaks.

About the Institution

Ranked in the top 9% of private US colleges that provide the best return on tuition investment, Pace University transforms the lives of its diverse students-academically, professionally, and socioeconomically. Currently, the University enrolls more than 13,000 students in more than 150 bachelor's, master's, and doctoral programs. Pace University is at the forefront of creating opportunity. Through the convergence of strong academics, experiential learning, and dedicated advising, Pace University empowers its students and positively impacts its communities.

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Pace University is excited to offer a unique opportunity for a motivated and skilled student to join a research project for the summer. The project focuses on identifying protective factors against dementia, and this position is ideal for students currently enrolled at Pace University who are looking to advance their analytical skills and gain significant professional experience in health research.

Key Responsibilities:

• Assist in data collection, analysis, and management.

• Utilize statistical software (STATA, SAS, R) for longitudinal data analysis.

• Collaborate closely with the research team to prepare findings for publication.

Benefits:

• Mentorship from Professor Lu Shi, a researcher with over 100 peer-reviewed publications.

• Potential to co-author a publication based on the research findings.

• Gain invaluable experience in a research setting that is actively contributing to understanding dementia.

Interested candidates should submit their resume and a brief cover letter outlining their qualifications and interest in the project. We look forward to receiving your applications and potentially welcoming you to our research team this summer!

Preferred Qualifications:

• Strong statistical training, particularly in longitudinal analysis.

• Familiarity with statistical software such as STATA, SAS, or R.

• Ability to work independently and as part of a team.

• Strong analytical and problem-solving skills.