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Open Postdoctoral position, faculty mentor Summer Han

Important Info

Faculty Sponsor (Last, First Name): 
Han, Summer
Stanford Departments and Centers: 
Biomedical Informatics
Epidemiology and Population Health
Biomedical Data Sciences
Neurosurgery
Postdoc Appointment Term: 
2 years (can be extended)
Appointment Start Date: 
ASAP
Group or Departmental Website: 
http://med.stanford.edu/summerhanlab.html
How to Submit Application Materials: 

Please email the required application materials to:
Summer Han, Ph.D. (summer.han@stanford.edu)
Associate Professor of Medicine, Neurosurgery, Epidemiology Quantitative Sciences Unit
Stanford Center for Biomedical Informatics Research (BMIR)
Stanford University School of Medicine
http://med.stanford.edu/summerhanlab.html

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: 
Over $70,000

Machine learning, Statistical genetics, and scRNA-seq data analysis
Applications are invited for postdoctoral fellow positions in statistical genetics, machine learning,  and predictive modeling to join Dr. Summer Han’s research group in the Stanford Center for Biomedical Informatics Research at Stanford University. This position emphasizes developing and applying statistical methods for analyzing genomic data (e.g., single-cell RNA-seq data, spatial transcriptomic data), for building machine-learning based prediction models for various cancers or neurodegenerative diseases using time-to-event outcomes or for novel natural language processing (NLP) to analyze imaging or free-text data generated from electronic health records (EHRs). Specific areas of interest include but are not limited to: (1) single-cell RNA seq data analysis, (2) spatial transcriptomic data, (3) whole-genomic sequencing data analysis, (4) dynamic risk prediction modeling for survival/competing risks data, (5) causal inference methods to analyze large observational data, and (6) NLP and AI methods to analyze EHR data.

Required Qualifications: 
  • We seek an individual with strong statistical and computing backgrounds.
  • Successful applicants should have a strong background in bioinformatics, biostatistics, or computational biology.
  • PhD degree
  • Hands-on experience in algorithmic implementation, statistical programming and data manipulation, using R/Bioconductor and contemporary, open-source bioinformatics tools and database structures.
  • Strong programming skill in R is required. 
Required Application Materials: 
  • A cover letter
  • CV
  • A short description of research interests
  • Contact information of three referees

 

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.