754 machine-learning-"https:" "https:" "https:" "UCL" "UCL" positions at Harvard University
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
PhD, and benefits can be found at https://postdoc.hms.harvard.edu/guidelines . With this appointment, you are represented by the Harvard Academic Workers (HAW) – UAW for purposes of collective
-
Number: 15996 School: Harvard Divinity School Position Description: Harvard Divinity School seeks an adjunct instructor/lecturer in Intermediate Coptic (2nd year of translation study) to teach an eight
-
opportunity to contribute to leading-edge research at the intersection of applied machine learning and clinical dental practice. As a member of our team, you will help translate contemporary data science
-
, discounts and campus perks Learn more about these and additional benefits on our Benefits & Wellbeing Page . EEO/Non-Discrimination Commitment Statement Harvard University is committed to equal opportunity
-
caregivers Professional development opportunities including tuition assistance and reimbursement Commuter benefits, discounts and campus perks Learn more about these and additional benefits on our Benefits
-
) is a community of Information Technology professionals committed to understanding our users and devoted to making it easier for faculty, students, and staff to teach, research, learn, and work through
-
) Foundry team and learners on our platform. This key technical role requires hands-on expertise across data science, machine learning, and AI solutions. You will manage the lifecycle of artificial
-
of the Ancient Near East (HMANE), the Collection of Historical Scientific Instruments (CHSI), and the Peabody Museum of Archaeology and Ethnology (PMAE). To learn more about HMSC's mission, objectives, and core
-
scientists, engineers, and/or doctors! The lab is committed to fostering lifelong learners in an environment that is diverse, inclusive and respectful. Learn more about our lab here: https
-
, and either flow cytometry or microscopy, or both. The ideal candidate values patience, curiosity, and hypothesis-driven science, and is eager to learn new model systems and/or techniques. High standards