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.