Postdoctoral Fellow in Riemannian Optimization

Postdoctoral Fellow in Riemannian Optimization

Title:

Postdoctoral Fellow in Riemannian Optimization

School:
Harvard John

A. Paulson School of Engineering and Applied Sciences

Department/Area:
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.

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.

Additional Qualifications:

[None specified]

Special Instructions:
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.

Contact Information: mwebervard.edu

Salary Range: $67,600 – $91,826

Pay offered to the selected candidate is dependent on factors such as rank, years of experience, training or qualification, field of scholarship, and accomplishments in the field.

Minimum Number of References

Required:

3

Maximum Number of References Allowed: 3

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