Open Postdoctoral position, faculty mentor Euan Ashley

Posted on Tue, 06/02/2026 - 11:38

Important Info

Faculty Sponsor First name: 
Euan
Faculty Sponsor Last Name: 
Ashley
Other Mentor(s) if Applicable: 
Gomes, Bruna
Stanford Departments and Centers: 
Medicine, Cardiovascular Medicine
Postdoc Appointment Term: 
One year (with option to reappoint)
Appointment Start Date: 
As soon as possible
Group or Departmental Website: 
https://ashleylab.stanford.edu/
How to Submit Application Materials: 

Email CV to Bruna Gomes @ bgomes@stanford.edu

Does this position pay above the required minimum?: 
No. The expected base pay for this position is the Stanford University required minimum for all postdoctoral scholars appointed through the Office of Postdoctoral Affairs. The FY27 minimum is $79, 056.

Postdoctoral Fellow in AI, Multi-Omics, and Heart Failure Discovery

We are seeking a postdoctoral fellow to work at the intersection of cardiovascular medicine, biomedical data science, artificial intelligence, genetics, imaging, and multi-omics discovery.

The fellow will help develop and apply computational approaches to study heart failure mechanisms and therapeutic targets using large-scale human datasets, including cardiovascular imaging, genetics, omics, EHR data, and clinical outcomes. Ongoing work builds on deep-learning phenotypes from cardiovascular imaging at population scale and extends toward myocardial tissue remodeling, fibrosis-enriched imaging phenotypes, multi-omic causal discovery, and AI-enabled target prioritization.
 

The fellow may also contribute to projects related to scientific discovery agents and AI-assisted workflows for biomedical research, as well as collaborative efforts within the NHLBI AI Data Science Center, a new initiative focused on AI-enabled precision medicine across heart, lung, blood, and sleep disorders.
 

Key responsibilities include:
 (1) Develop and apply computational methods for heart failure discovery.
 (2) Analyze large-scale human datasets, including imaging, genetics, omics, EHR, and outcomes data.
 (3) Build reproducible pipelines for datasets such as UK Biobank, All of Us, TOPMed/MESA, and Stanford clinical data.
 (4) Collaborate with multidisciplinary teams across cardiovascular medicine, biomedical data science, genetics, and AI.
 (5) Lead and contribute to peer-reviewed manuscripts, conference presentations, and grant proposals.

Required Qualifications: 
  • PhD, MD, MD/PhD, or equivalent doctoral degree in biomedical data science, computational biology, genetics, bioinformatics, machine learning, computer science, statistics, engineering, medicine, or a related field.
  • Strong candidates may have experience with large-scale human datasets, machine learning, statistical genetics, causal inference, multi-omics, cardiovascular imaging, programming in Python or R, and scientific writing.
  • Prior experience in cardiovascular medicine is welcome but not required.
  • We are especially interested in applicants who are intellectually curious, rigorous, collaborative, creative, and motivated to ask meaningful biological and clinical questions using complex human data.
Required Application Materials: 
  • CV
  • Brief cover letter describing research experience and interests
  • 2-3 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.