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Postdoctoral Fellow in Geometric Machine Learning
Harvard University in Cambridge, Massachusetts
 
 
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Date Posted November 04, 2022
Category
Admin-Tutors and Learning Resources
Employment Type
Application Deadline Open until filled
 
 
 
 
 

Details


Title Postdoctoral Fellow in Geometric Machine Learning
School Harvard John A. Paulson School of Engineering and Applied Sciences
Department/Area Applied Mathematics
Position Description
A postdoctoral position is available in Melanie Weber’s group at Harvard University. The group works at the intersection of Geometry and Machine Learning, with a focus on recognizing and exploiting geometric structure in data and models.
Research areas include Representation Learning, Machine learning and Optimization on Graphs and Manifolds, as well as applications of geometric methods in the sciences. For more information and recent publications, see http://melanie-weber.com/ . For questions, please email mweber@seas.harvard.edu . This is a one-year position, with possible extension. The start date is flexible, but ideally around August 2023.
Review of applications will begin in January 2023, but applications will be accepted until the position is filled.
Basic Qualifications
A Ph.D. in Mathematics, Computer Science, or a related field, by the start of the appointment.
Additional Qualifications
Special Instructions
Please submit your CV, a research statement, names and contact information of at least 3 references, as well as copies of two publications that are representative of your work and research interests. SEAS is dedicated to building a diverse and welcoming community and strongly encourages applications from historically underrepresented groups.
Contact Information
Melanie Weber
c/o Melissa Majkut
29 Oxford Street, Pierce 222
Cambridge, MA 02138
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
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