Postdoctoral Fellowships in Networking Support for Machine Learning

Postdoctoral Fellowships in Networking Support for Machine Learning

Title: Postdoctoral Fellowships in Networking Support for Machine Learning

School: Harvard John A. Paulson School of Engineering and Applied Sciences

Department: Computer Science

The John A. Paulson School of Engineering and Applied Sciences at Harvard University (SEAS) seeks applicants for a postdoctoral position in networking support for machine‑learning systems. The initial term for this position is one year; reappointment for a second year is contingent upon funding.

The postdoc will work closely with Minlan Yu and other group members focused on networking support for machine‑learning systems, as well as possibly other Harvard faculty.

The candidate will be expected to publish scholarly papers, attend internal, domestic, and international conferences and meetings, and take on a mentorship role for undergraduate and graduate students.

Basic Qualifications

Candidates are required to have a doctorate or terminal degree in Computer Science or a related area by the expected start date.

Additional Qualifications

None provided.

Contact Information

Contact Email: [email protected]

Salary Range

$67,600 – $91,826

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

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