Kubelt
Postdoctoral Fellow in Geometric Machine Learning
Kubelt, Harvard, Illinois, United States, 60033
The Protocol Labs Network is an ecosystem of teams pushing the boundaries of decentralized technologies, research, and open‑source innovation. Explore opportunities across the network and join the mission.
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 , 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. 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.
Application 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.
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
EEO/Non-Discrimination Commitment Statement Harvard University is committed to equal opportunity and non-discrimination. We seek talent from all parts of society and the world, and we strive to ensure everyone at Harvard thrives. Our differences help our community advance Harvard’s academic purposes. Harvard has an equal employment opportunity policy that outlines our commitment to prohibiting discrimination on the basis of race, ethnicity, color, national origin, sex, sexual orientation, gender identity, veteran status, religion, disability, or any other characteristic protected by law or identified in the university’s non-discrimination policy. Harvard’s equal employment opportunity policy and non-discrimination policy help all community members participate fully in work and campus life free from harassment and discrimination.
Supplemental Questions Required fields are indicated with an asterisk (*).
#J-18808-Ljbffr
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 , 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. 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.
Application 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.
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
EEO/Non-Discrimination Commitment Statement Harvard University is committed to equal opportunity and non-discrimination. We seek talent from all parts of society and the world, and we strive to ensure everyone at Harvard thrives. Our differences help our community advance Harvard’s academic purposes. Harvard has an equal employment opportunity policy that outlines our commitment to prohibiting discrimination on the basis of race, ethnicity, color, national origin, sex, sexual orientation, gender identity, veteran status, religion, disability, or any other characteristic protected by law or identified in the university’s non-discrimination policy. Harvard’s equal employment opportunity policy and non-discrimination policy help all community members participate fully in work and campus life free from harassment and discrimination.
Supplemental Questions Required fields are indicated with an asterisk (*).
#J-18808-Ljbffr