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Harvard Machine Jobs (NOW HIRING)

Harvard University

Visitor in Public Policy

Cambridge, MA · On-site

$170K - $185K/yr

... Machine Learning, and Artificial Intelligence We will begin considering applications on March 1, and we will continue to do so until the positions are filled. Harvard University is committed to equal ...

Harvard University

Property Administrator

Cambridge, MA · On-site

$22 - $29.50/hr

... for vending machines, building access system, etc.; implements building-wide recycling programs as appropriate. * Implements requested changes in the Harvard CCure building access systems.

Harvard University

Assistant Property Manager

Cambridge, MA · On-site

$20.50 - $27.75/hr

Harvard University Housing & Real Estate Harvard University Housing & Real Estate (HUHRE) is a ... for vending machines, building access system, etc.; implements building-wide recycling and ...

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How much do harvard machine jobs pay per hour?

As of Jun 2, 2026, the average hourly pay for harvard machine in the United States is $26.35, according to ZipRecruiter salary data. Most workers in this role earn between $21.39 and $27.88 per hour, depending on experience, location, and employer.

Postdoctoral Fellow in Geometric Machine Learning (Harvard)

Kubelt

Harvard, IL • On-site

$46.60K - $63.30K/yr

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

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 (*).

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