A postdoctoral position is available in the Geometric Machine Learning Group at Harvard University, led by Prof. Melanie Weber. This role offers an opportunity to perform research at the intersection of Geometry and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees. Research areas include Representation Learning, Machine learning and Optimization on graphs and manifolds, as well as applications of geometric methods in the Sciences.
This is a one-year position with the possibility of extension. The preferred start date is July 1, 2025, though there is some flexibility.
For more details on our research and recent publications, see the Geometric Machine Learning Group’s website: https://weber.seas.harvard.edu
For questions, please email mweber@seas.harvard.edu .
Applications will be reviewed on a rolling basis, starting December 15. The position will remain open until filled.
Basic Qualifications
A Ph.D. in Mathematics, Computer Science, or a related field, by the start of the appointment.
To apply, please submit the following materials:
CV
Research Statement outlining your current and future research interests
Three Reference Letters
Copies of two publications representative of your work and research interest
