Harvard University
Postdoctoral Fellow in Geometric Machine Learning
Harvard University, Cambridge, Massachusetts, us, 02140
Postdoctoral Fellow in Geometric Machine Learning
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 , focusing 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. The preferred start date is
July 1, 2025 , though there is some flexibility. Application Review:
Applications will be reviewed on a rolling basis, starting December 15. The position will remain open until filled. 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: CV Research Statement
outlining your current and future research interests Three Reference Letters Copies of
two publications
representative of your work and research interest SEAS is dedicated to building a diverse and welcoming community. 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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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 , focusing 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. The preferred start date is
July 1, 2025 , though there is some flexibility. Application Review:
Applications will be reviewed on a rolling basis, starting December 15. The position will remain open until filled. 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: CV Research Statement
outlining your current and future research interests Three Reference Letters Copies of
two publications
representative of your work and research interest SEAS is dedicated to building a diverse and welcoming community. 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
#J-18808-Ljbffr