275 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "UNIV" "Univ" "Univ" "Univ" research jobs at Harvard University
Sort by
Refine Your Search
-
Listed
-
Program
-
Field
-
that arise, and contribute intellectually to the project. For more information, visit: https://wyss.harvard.edu/focus-area/biomimetic-therapeutic-diagnostics/ What you'll do: Perform microfluidic organ-on-chip
-
position in the Gozzi Lab at the Rowland Institute at Harvard (https://www.rowland.harvard.edu/). Our lab’s primary focus is on bacterial-encoded domesticated viruses, known as gene transfer agents
-
collaborative, impact-focused problem solver who wants to be part of a dynamic team. Information about the Shih Lab: Learn more about the innovative work led by Dr. William Shih here: https
-
brain slicing using a cryostat, staining for proteins using immunohistochemical techniques, identifying RNAs via in situ analysis, etc. Analyzing data and presenting results at lab meetings and during one
-
," and we love challenges. For more information discover our technologies , catch up on our recent news , or watch our latest videos . Job Description About you: You are a collaborative, impact-focused
-
, for our excellent leadership, and we are a strong community that values diversity. For more information about HGSE, its programs, research, and faculty, please visit: www.gse.harvard.edu . Job Description
-
: January 9, 2026 For more information, see http://warrencenter.fas.harvard.edu/. Basic Qualifications Applicants may not be degree candidates and should have a Ph.D. or equivalent. Fellows have library
-
Qualifications Special Instructions Interested candidates should submit a cover letter, CV, a brief research proposal, and two to three references’ names and contact information. Applications will be reviewed on a
-
attraction to artificial light that took place over summer 2025. Candidates will be expected to plan and lead behavioral experiments; acquire and analyze relevant data; supervise and mentor undergraduate
-
Postdoctoral Fellow with Professor Morgane Austern. Professor Austern’s group focuses on research in high-dimensional statistics, probability theory, machine learning theory, graph data, Stein method, ergodic