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Open Postdoctoral position, faculty mentor Gary Peltz

Important Info

Faculty Sponsor (Last, First Name): 
Peltz, Gary
Stanford Departments and Centers: 
Postdoc Appointment Term: 
Appointment Start Date: 
How to Submit Application Materials: 

To apply, please submit the following to

Post-doctoral Fellow: Biostatistics and Bioinformatics
The Peltz Laboratory at the Stanford University School of Medicine has multiple biomedical discovery programs, which generate complex datasets using advanced genetic and genomic methodology, that include: (i) Computational genetic analysis of multiple mouse models examining responses to drugs of abuse (cocaine, opiates and nicotine) that are generated by a multi-center (UO1) project; (ii) Developing artificial intelligence methods for genetic discovery; (iii) Analysis of human liver organoids to identify novel pathways affecting liver development, and for liver cancer treatment; (iv) A multi-center clinical trial that tests a new therapy, which emerged from a computational mouse genetic discovery, for preventing withdrawal in babies born to mothers that consume opiates; (v) Pharmacokinetic and metabolomic data obtained from mice with humanized livers, and from human subjects, using a new microcapillary sampling method. For each project, whole genome sequence, single-cell RNA-sequence, and/or metabolomic datasets are analyzed in an integrative fashion.
Responsibilities include:

  • Perform statistical and research for the above studies. This includes participating in study design; and performing data modeling, data analysis, and data management.
  • Developing new (or improved) methods for computational genetic research and AI-based discovery
  • Projects analyzed include big data/AI research for genetic mapping (using the mouse as the model organism); characterizing developmental systems using scRNA-seq and metabolomic data sets
  • Provide statistical analysis for evaluating traditional biologic experiments
Required Qualifications: 
  • Ph.D. in Biostatistics, Statistics, or a related field
  • Capable of functioning independently, but a demonstrated ability to work collaboratively
  • Experience with multiple statistical programming languages such as R, SAS and Python
  • A demonstrated ability to communicate with a range of different audiences
  • Skilled in data modeling and the use of graphic interfaces
  • Demonstrated expertise (publications) with statistical and bioinformatic methodology


  • Experience with analysis of large scale genetic, metabolomic or scRNA-seq data
  • Proven history of developing novel statistical or bioinformatic methodology
Required Application Materials: 
  • A CV that emphasizes your bioinformatic/biostatistical experience and accomplishments
  • List two individuals that will serve as references


Stanford is an equal opportunity employer and all qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by law.