Assistant Director of Computational Biology @ Stanford University School of Medicine

January 25, 2022

The Quantitative Sciences Unit (QSU) is an interdisciplinary collaborative statistics unit in the Biomedical Informatics Research Division within the Department of Medicine at Stanford University. The mission of the QSU is to facilitate cutting-edge scientific studies initiated by Stanford investigators by providing expertise in biostatics and informatics, to mentor and educate clinical investigators in research methods and to mentor data scientists. To optimally achieve this mission, the QSU members become fully integrated into individual research teams.

The QSU is looking for an Assistant Director of Computational Biology to lead and further build our computational biology team. Working closely with other researchers and data scientists in our QSU organization, the candidate will lead the application—and inform the development—of the state-of-the-art computational biology program within the QSU. We are seeking a highly motivated, hard-working and professional computational biology data scientist and leader to further build our team of collaboration with clinical, immunological and basic science researchers. We generate and have access to clinical and immunological data as well as many large data sets, including mass cytometry (CyTOF) and single cell and bulk sequencing data (e.g. RNA-Seq, ATAC-Seq). The successful candidate will join a vibrant team of academic data scientists and statisticians working on a wide variety of collaborative projects in medicine. The successful candidate will provide the high-level strategy for the computational and analytical framework and execution within the QSU organization. This position holds excellent career development opportunities. This is a senior academic staff position.

Duties include:

  • Build and oversee the QSU’s Computational Biology program
  • Lead computational biology studies to address important biomedical questions including: designing the study, the analysis plan and carrying out the statistical programming and data management to implement the plan.
  • Lead methodological projects to contribute to the development of novel computational biology tools necessary for collaborative research.
  • Oversee a team of both senior-level and junior-level data scientists on the creation of pipelines, the cleaning and management of data, the design and analysis of complex studies, and the mentorship of  data scientists in the area of conducting collaborative computational biology research.
  • Collaborate with clinical and lab-based investigators on campus including the Heart Center, the Department of Medicine, the Department of Neurosurgery, and the Stanford Cancer to independently design studies and develop analysis plans. More specifically, the incumbent will meet one-on-one with the collaborator to gain background on the study and the research questions and help to refine the questions and formulate the hypotheses.  The incumbent will also extract necessary information to design the study with optimal operating characteristics and to develop a sound analysis plan.  
  • Develop oral and written dissemination of findings for meetings with collaborators or for medical and/or statistical journal articles.  The incumbent is also expected to develop lectures on statistical methods or statistical programming for the training of clinical investigators as needed and for the training of junior biostatisticians.  In addition, the incumbent will participate in developing and writing grant proposals.



  • Ph.D. in Computational Biology, Biostatistics, Statistics, Bioinformatics or related field.
  • Capable of functioning independently and collaboratively at an advanced level under the overall direction of the QSU Director.
  • Experience with multiple programming languages such as Python and R.
  • Outstanding oral and written communication skills with the ability to communicate technical information to all audiences.
  • Skilled in descriptive analysis, modeling of data, and graphic interfaces.
  • Demonstrated expertise in analytic tools.
  • At least five years of experience collaborating as a computational biologist or biostatistician is desirable.



  • Experience supervising technical staff including training, mentoring and coaching.
  • Experience developing and writing grant proposals.  
  • Experience in single cell data analyses and integrative multi-omics approaches is a strong plus.
  • A background in immunology and experience working with clinical trial data will be a plus and will help in the development of independent research projects.


To apply, please send your CV and Cover Letter to:


Why Stanford is for You:
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