Details 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. 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. 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 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 Melanie Weber Contact Email mweber@seas.harvard.edu Equal Opportunity Employer Harvard is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, sex, gender identity, sexual orientation, religion, creed, national origin, ancestry, age, protected veteran status, disability, genetic information, military service, pregnancy and pregnancy-related conditions, or other protected status. Minimum Number of References Required 3 Maximum Number of References Allowed 3 Keywords Supplemental Questions