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Harvard University

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Great balance, positive atmosphere but not great for advancement or development - Senior Software Engineer Harvard University Employee Review

4.0
Mar 14, 2012
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Pros

The benefits, hours, and general work environment are great. There are a lot of available resources (libraries, gyms, discounts, etc.) and Harvard Square is a great area. Management is supportive and seems genuinely interested in moving the IT organization forward. It is a great place for people with families, a friendly atmosphere and the stress levels are relatively low.

Cons

Things change at a glacial pace which can be a problem when working with technology. The pay is below industry standard and this has been getting worse in recent years. The perks and benefits used to partially make up for it but this is no longer true in my opinion. It can be very hard to move up at Harvard because there is very little turnover or growth. When opportunities do open up they seem to frequently hire from the outside. There are a wide range of IT activities going on but it's very hard to get involved or even learn about them because groups are very silo'd. There does seem to be an expressed desire to change some of these things from upper management but this has also been expressed in the past and I'm not optimistic that this will happen quickly.

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5.0
Jun 25, 2026
Recommend
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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
Jun 3, 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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