| Title | Postdoctoral Fellow in Geometric Machine Learning |
|---|---|
| School | Harvard John A. Paulson School of Engineering and Applied Sciences |
| Department/Area | Applied Math |
| 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 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.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. |
| Basic Qualifications | A Ph.D. in Mathematics, Computer Science, or a related field, by the start of the appointment. |
| Additional Qualifications | |
| Special Instructions | To apply, please submit the following materials:CVResearch Statement outlining your current and future research interestsThree Reference LettersCopies of two publications representative of your work and research interestSEAS is dedicated to building a diverse and welcoming community. |
| Contact Information | For more details on our research and recent publications, see the Geometric Machine Learning Group’s website: https://weber.seas.harvard.edu |
| 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
Required fields are indicated with an asterisk (*).
Applicant Documents
Required Documents
- Curriculum Vitae
- Cover Letter
- Statement of Research
- Publication
- Publication 2
Optional Documents
- Publication 3