Non-tenure-track/postdoctoral Stanford, United States Apply
Job
Stanford University
SUNCAT Center for Interface Science and Catalysis
443 Via Ortega
94305 Stanford
United States

Applications are invited for a postdoctoral position at the SUNCAT Center for Interface Science and Catalysis at SLAC National Accelerator Laboratory / Stanford University. The successful candidate will play an important role in developing machine learning models predicting the stability, activity, and selectivity of heterogeneous catalysts by combining experimental and computational data. A particular emphasis in the project will be the discovery of human-interpretable ML models that will enable developing an atomic-level understanding of catalytic processes under realistic experimental conditions.

As the successful candidate, you will have:

  • A PhD in mathematics, computer science, physics, chemistry, materials science, or related field
  • A strong background in machine learning, computational physics, or chemistry
  • Proficiency in programming and data analysis with Python
  • Excellent communication skills
  • The ability to work independently and collaboratively in a diverse research team

The position is open now and it is initially for one year with possibility of extension for another year based on performance, mutual consent, and anticipated continued funding.

Preview of applications begins immediately.

Contact:
Dr. Johannes VossĀ  vossj@stanford.edu
https://web.stanford.edu/group/suncat/vossgroup/


Application Instructions

Interested applicants are encouraged to apply via email to

Dr. Johannes VossĀ  vossj@stanford.edu

Please include a letter of motivation, C.V. with list of publications, and the contact information for two to three academic references.


(Add to Calendar)
This employer is not accepting applications through MathHire.org. Please follow the instructions above and refer to MathHire.org in your application.
Contact Person
Dr. Johannes Voss