Postdoctoral Fellow in Riemannian Optimization

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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.

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

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

To apply, please submit the following materials:

• CV
• Two‑page Research Statement outlining your current and future research interests
• Three Reference Letters

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

Harvard John

A. Paulson School of Engineering and Applied Sciences

Contact Email: mwebervard.edu

$67,600 – $91,826

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