-
or MD/PhD Strong programming skills, preferably in R and/or Python Previous expertise and/or interest in single-cell sequencing technologies, bioinformatics, spatial analyses, and generative AI is desired
-
to work independently and as part of a multidisciplinary team. Experience in metabolomics, proteomics, or lipidomics. Familiarity with bioinformatics and statistical tools for LCMS data analysis. Prior
-
willing to learn, CyTOF, sequencing-including NGS and RNA-Seq, and bioinformatics. The candidate must be quick to learn new techniques and be able to modify and adapt standard protocols. The candidate
-
bioinformatics tools for data analysis Required Application Materials: Curriculum Vitae Stanford is an equal opportunity employer and all qualified applicants will receive consideration without regard to race
-
and cancer. Individuals with backgrounds in stem cell biology, cancer biology, molecular biology, immunology, and bioinformatics, are all welcome to apply. Lab techniques include mammalian cell culture
-
Bioinformatics, computational analysis is preferable. Excellent communication skills and fluency in spoken and written English. Required Application Materials: Cover letter that describes your research interests
-
chromatin structured contexts. Ideal for those with experience in cell culture, molecular biology, and seeking to acquire or strengthen expertise in gene editing methodologies, bioinformatics, and DNA DSB
-
Postdoctoral Affairs. The FY25 minimum is $73,800. We are seeking a highly motivated and skilled Postdoctoral Fellow in Bioinformatics to join our dynamic research team. The primary focus of the research will be
-
should have a strong background in cancer biology, molecular biology, biochemistry, immunotherapy/immunology, bioinformatics, and experience working with mammalian cells and mouse models of cancer
-
techniques, and bioinformatics analysis is welcomed. The candidate is expected to work independently, as part of a team, and collaboratively with other researchers. An individual who demonstrates self