Please email application to Dr. Zihuai He (email@example.com). Applications will be reviewed immediately after submission.
The research group led by Dr. Zihuai He (https://profiles.stanford.edu/zihuai-he) at Stanford University is recruiting postdoctoral scholars with prior training in statistics, biostatistics, computer science, bioinformatics or a closely related area. Applications are invited from ambitious, independent and motivated candidates with a strong publication record.
Dr. He’s group develops statistical and computational methodologies for the identification and interpretation of functional gene mutations/variants that cause or contribute to the risk of or protection against the development of Alzheimer’s disease (AD) and Alzheimer's disease related dementias (ADRD) via analysis of a variety of genetic, genomic, and biomarker data that are currently available to the research community.
The postdoctoral scholars will be working on three core research topics: 1) develop novel statistical methods for analyzing and extracting information from large/biobank scale genetic data; 2) develop scalable and interpretable AI methods that lead to the identification of functional gene mutations/variants involved in AD pathogenesis. 3) develop pipeline to apply such methods to analyze large heterogeneous datasets. They will also be encouraged to develop and pursue their own lines of inquiry.
Dr. Zihuai He is a dedicated mentor with a particular interest in helping young scientists build their careers in academia, industry, and beyond. Our group is well-suited to young scientists who are interested in the development of modern statistical and computational methods and/or learn how to better apply their skills toward the alleviation of human disease.
• Completed (or nearly completed) a PhD in Statistics, Biostatistics, Computer Science, Bioinformatics, or a closely related area prior to their appointment.
• Strong programming skills (R, Python, etc.).
• Excellent written and oral communication skills.
• Experience in statistical genetics, machine learning or deep learning is preferred.
1. Cover letter describing your interest in applying to the lab.
2. Curriculum vitae.
3. Contact information for 3 professional references.
4. Your most recent or relevant publications.