Join Our Group:  We have openings for highly motivated postdoctoral scholars 

Postdoctoral candidates should have R statistical software expertise and experience in executing and interpreting machine learning algorithms and using epidemiological data. Projects include analyses of existing large scale -omics data such as genome-wide DNA methylation, transcriptomics and epigenetic aging from multiple human cohorts and studies. The candidate will have access to a vibrant research community at Stanford, data science experts, methodologists and join a dynamic research team. The scholar will have access to pilot funding and data to further develop an independent research career. The scholar will work in a multidisciplinary collaborative environment. 

Preferred qualifications: 

• PhD in one of a variety of fields, including but not limited to epidemiology, biostatistics, or environmental health. 

• Experience using R statistical software. 

• Experience with epidemiological analyses and application of machine learning methods. 

• Previous experience with analyses of large-scale DNA methylation data is desirable, bioinformatics and using Bioconductor. 

• Proven record of scientific publications.

 Responsibilities: 

• Apply machine learning algorithms and estimation methods to existing epidemiological data. 

• Execute analyses of existing large scale -omics data such as genome-wide DNA methylation, transcriptomics and epigenetic aging from multiple human studies. 

• Expected to report results at scientific conferences and disseminate findings in publications. 

 

Applicants should submit a CV and cover letter that describes their professional qualifications along with contact information for three references. Please submit the CV and cover letter to Alex Garcialuna: agar264@stanford.edu.