Description

Harvard University


Title: Postdoctoral Fellow in Riemannian Optimization

School: Harvard John A. Paulson School of Engineering and Applied Sciences


Position Description: 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 on Riemannian Optimization. The ideal candidate has a strong background in this area, as well as a genuine interest in continuing such work.

This is a one-year position with the possibility of extension. The start date is flexible.

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 [email protected]

Applications will be reviewed on a rolling basis. The position will remain open until filled.

Basic Qualifications: A Ph.D. in Mathematics, Applied Mathematics, Computer Science, or a related field, by the start of the appointment.


Special Instructions: To apply, please submit the following materials:

1. CV;
2. Two-page Research Statement outlining your current and future research interests;
3. Three Reference Letters;

Copies of two publications representative of your work and research interests, ideally related to Riemannian Optimization.

Contact Information: Melanie Weber

Contact Email: [email protected]


Minimum Number of References Required: 3

Maximum Number of References Allowed: 3


Supplemental Questions: Required fields are indicated with an asterisk (*).

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