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Open Postdoctoral position, faculty mentor Pascal Geldsetzer

Important Info

Faculty Sponsor (Last, First Name): 
Geldsetzer, Pascal
Other Mentor(s) if Applicable: 
Stefano Ermon, Marshall Burke, David Lobell, Gary Darmstadt, Eran Bendavid
Stanford Departments and Centers: 
Medicine: Primary Care and Population Health
Environ Earth System Science
Computer Science
Epidemiology and Population Health
Postdoc Appointment Term: 
1-3 years (negotiable)
Appointment Start Date: 
negotiable
Group or Departmental Website: 
https://profiles.stanford.edu/pascal-geldsetzer
http://sustain.stanford.edu
https://cs.stanford.edu/~ermon/website/
How to Submit Application Materials: 

Please apply by sending a CV to Pascal Geldsetzer at pgeldsetzer@stanford.edu. A cover letter is not required. There is no specific deadline for the application – we hire on an ongoing basis.

Deep learning in satellite imagery to monitor health indicators in low- and middle-income countries
 
This postdoctoral fellowship is a collaboration between Stanford University and the Heidelberg Institute of Global Health at Heidelberg University, Germany’s oldest university and a leading hub for health-related research in Europe. We are looking for a researcher with experience working with convolutional neural networks and, ideally, satellite imagery. The researcher will work under the mentorship of Drs. Pascal Geldsetzer, Stefano Ermon, David Lobell, Marshall Burke, Gary Darmstadt, and Eran Bendavid, as well as other researchers at Stanford and Heidelberg University.
 
The Postdoctoral Research Fellow will process and analyze satellite data. The broad aim of these analyses is to devise novel ways of using machine learning in satellite data for assessments of health indicators and to improve healthcare delivery in low- and middle-income countries. The researcher will be expected to publish in leading peer-reviewed journals.

Required Qualifications: 
  • Doctoral degree with training (or research experience) in convolutional neural networks and/or the analysis of satellite image data. 
  • Strong coding skills in Python or R.
  • Good communication skills in English.
Required Application Materials: 
  • CV

 

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.