Posted on Fri, 06/07/2024 - 14:14

Important Info

Faculty Sponsor (Last, First Name): 
Plevritis, Sylvia
Stanford Departments and Centers: 
Biomedical Data Sciences
Postdoc Appointment Term: 
Two to three years. Can be extended.
Appointment Start Date: 
As soon as possible
Group or Departmental Website: 
https://plevritislab.stanford.edu/
How to Submit Application Materials: 

Please complete our questionnaire and upload your documents here for your applications to be considered.   Please don't send your documents via email. Applications will be accepted until the position is filled.
 

Does this position pay above the required minimum?: 
Yes. The expected base pay range for this position is listed in Pay Range field. The pay offered to the selected candidate will be determined based on factors including (but not limited to) the qualifications of the selected candidate, budget availability, and internal equity.
Pay Range: 
$74,128 - $75,611

Postdoctoral Fellowship in Computational Spatial Biology - Plevritis Lab

We are seeking a postdoctoral fellow in computational spatial biology to work in the laboratory of Professor Sylvia Plevritis in the Department of Biomedical Data Science at Stanford University. This research opportunity will be focused primarily on the development and application of novel computational algorithms to analyze and integrate diverse omics datasets, including single-cell RNA-seq, spatial transcriptomics and multiplexed immunofluorescence in-situ images, in the study of immune-stromal-cancer interactions in metastatic progression. The scholar will aim to understand mechanisms through which the tumor microenvironment impacts tumor invasion and metastatic progression, using high-throughput data derived from cellular subpopulations within tumors. The individual will work closely with experimental biologists to translate computationally-derived results into experimentally testable hypotheses and analyze the resulting data from the experiments.

Required Qualifications: 
  • Candidate must have a strong quantitative background, with a PhD in computational biology, bioinformatics or related field including bioengineering, computer science, statistics, or mathematics.
  • Strong knowledge in bioinformatics, machine learning, statistics and programming skills (R, Python, or MATLAB) are required.
  • The ideal candidate should demonstrate a record of publications in the area.
  • Knowledge in one or more of the following areas is desirable: single-cell profiling technologies, spatial omics data, immunology and cancer systems biology.
  • Excellent verbal and written communication skills are essential.
Required Application Materials: 
  • Cover letter describing relevant research experiences, accomplishments, interests, and goals
  • Curriculum vitae
  • Name and contact information of three 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.