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Harvard University

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Experiences here vary widely - Anonymous employee Harvard University Employee Review

2.0
26 July 2013
Anonymous employee
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Pros

This is an endlessly interesting institution where high value is placed on learning, professional development, and taking advantage of the intellectual and cultural resources that Harvard offers. Excellent vacation, sick, and personal time.

Cons

As an enormous institution, professional experiences can vary widely. Be very careful about the specific environment you join there. I worked in a department that allowed an assistant vice president to treat staff disrespectfully and harshly, despite several legitimate concerns voiced to Human Resources and other senior leaders about this manager's demeaning behavior. In addition to this unfortunate staffing dynamic, the office in question (the central Development department) is not well-coordinated and strategic priorities/plans are ambiguous at best. This office could learn a lot from some of its peers in terms of running a more modern, efficient and respectful fundraising enterprise.

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5.0
25 June 2026
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Pros

A PhD is always very advisor/PI dependent, but I had a great experience with room to learn, grow, and explore interesting research questions. As with any PhD program you’ll work pretty hard for relatively lower pay and perhaps less directly applicable industry career trajectory at the end, but if you find good people to tackle the journey with and get to work on interesting problems I personally think the journey is worthwhile!

Cons

Less of a program wide cohort in my particular engineering field. Some funding challenges with the govt last year but seem mostly back now, apart from the recent administration issues funding wasn’t generally a challenge

5.0
3 June 2026
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Pros

You work with experts from every field possible in science from Mechanobiology to Metallurgy and working as a ML intern along with scientists from different fields gave me a lot of exposure and how to work in a research department.

Cons

One challenge encountered was maintaining a clear focus on training objectives, as the evolving parameters required continuous reassessment of the model's learning priorities. Additionally, the absence of established ground truth for the domain presented a limitation in validating and guiding the approach effectively.

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