Job:Postdoc in Bioinformatics (UCSF Benioff Children's Hospital Oakland)
Entering edit mode
djawaheer • 0
Last seen 5.5 years ago


Our lab is interested in transcriptome and epigenetic changes that occur in a time-dependent manner during pregnancy and how those can influence autoimmune disease. We are seeking a highly motivated and creative postdoctoral fellow to examine changes in coding and non-coding RNA patterns over time (based on RNA-seq data) in the context of human pregnancy and autoimmune disease. The successful applicant will perform original research in computational biology, assessing computational methods and developing/implementing analytical pipelines to infer underlying molecular mechanisms. He/She will take a lead in the project management, data analysis and interpretation of results within the context of the biological problem being investigated, and will collaborate with other team members. The ideal candidate is expected to report the scientific results by writing scientific papers and effectively communicate with peers. For more information about the project, see lab info.


Applicants must have a Ph.D. in bioinformatics, computational biology, statistics, human genetics or related field, and a sound understanding of biology, data science and statistical modeling. Must be proficient in statistical and programming languages such as R and Python, and familiar with Linux and high performance computing. Preference will be given to candidates with prior experience in analyses of RNA-seq data, other omics data, co-expression analyses, and with a thorough understanding of biological systems. Strong problem solving abilities and excellent verbal and written communication skills are required.

To Apply:

Please email cover letter, curriculum vitae, and the names and contact info of three references to: Damini Jawaheer, Ph.D. (djawaheer[at]

Bioinformatics RNA-seq Postdoc Genomics Statistical model Job • 1.1k views

Login before adding your answer.

Traffic: 529 users visited in the last hour
Help About
Access RSS

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6