Computational Associate – Genetic Epidemiology and Statistical Genetics (closed)

Dr. Zhi Yu and Dr. Michael Honigberg are jointly seeking two motivated and skilled computational associates to join their interdisciplinary research teams. These positions offer a unique opportunity to work on cutting-edge genetic epidemiology and statistical genetics projects, with potential focuses on polygenic risk score development, rare variant analysis, genetic association studies, and classical epidemiology.

Position Overview:

Depending on expertise and interests:

• One associate will work on polygenic risk score development, rare variant analysis, and genetic association studies.
• The other will focus on classical epidemiology work.
• This role is ideal for post-bachelor or post-master students looking to gain hands-on research experience, build their publication record, and explore research opportunities before applying to PhD programs. Both Dr. Yu and Dr. Honigberg have robust publication records and are committed to providing comprehensive training, guidance in research and writing, and opportunities for collaboration and presenting research work.

Key Responsibilities:

• Perform genetic and epidemiological data analyses, with a focus on polygenic risk scores, rare variants, or classical epidemiology.
• Collaborate with an interdisciplinary team, including researchers at Massachusetts General Hospital (MGH), Harvard Medical School, and the Broad Institute of MIT and Harvard.
• Participate in scientific writing and contribute to publications.
• Present research findings at internal and external meetings.

Qualifications:

• Master’s degree in genetic epidemiology, biostatistics, statistics, or a related field (Bachelor’s degree with relevant experience will also be considered).
• (Preferred but not required) Experience analyzing genetic and genomic data, such as genome-wide association studies (GWAS) or rare variant analysis.
• Strong programming skills (e.g., R, Python).
• Excellent organizational, communication, and collaborative skills.
• Self-motivated and driven to contribute to scientific research.

Why Join Us?

This position provides the opportunity to:

• Work in a dynamic and collaborative environment at the intersection of genetics, epidemiology, and computational biology.
• Be part of an innovative research community with access to world-class resources at MGH, Harvard Medical School, and the Broad Institute.
• Receive mentorship and hands-on training from leading experts in the field.
• Develop a strong publication record, valuable for future academic or professional pursuits.

Apply: Please contact Zhi via email (zyu5@mgh.harvard.edu) with your CV, a short introduction, and details of your research experience. Salary will be competitive compared to similar roles.