Qualitative Reputations of Top Biostatistics Programs?

[LacroixBoix]

I've been attempting to do some research into Biostatistics programs and was wondering if anyone has some insight into some of the qualitative differences between the top programs. I've found that program websites usually have very similar descriptions of their PhD programs, making it difficult to evaluate the differences between them. From USNWR I've found that the top 6 programs are Harvard, Hopkins, UW, UNC-Chapel Hill, Michigan, and UC Berkeley but aside from rank what are the different qualitative merits of each program?

 

For example, what are each of these programs known for? Do they have any differences in academic focus or pedagogy? Do they specialize in any specific area of study? Does placement of graduates differ meaningfully between them? Do they attract different kinds of students/faculty? 

 

My general feeling is that Harvard and Hopkins are more oriented towards private sector/clinical trials, UNC-Chapel Hill and Michigan (perhaps because they are public schools) are more directed towards the public sector, and UW and Berkeley have closer ties to silicon valley type work. This could be completely wrong though. Obviously there's not going to be a hard rules about any of these programs, just looking for more insight into the differences among them (as well as other programs I might have missed). Thanks!

[cyberwulf]

Here are some things which come to mind when I think about these programs. Of course, this is based on my observations (and narratives from others) and hence entirely subjective:

Harvard: Light coursework, heavy emphasis on research. Can be competitive. Many graduates end up in Harvard-affiliated non-faculty (or contract faculty) positions.

Hopkins: Heavy coursework. Fun environment (at least inside the building). Most well-known advisors very "data science"-y. 

UW: Heavy coursework. Fun student experience. Thin on advisors that don't do variable selection/machine learning. Students tend to graduate with a broad background but few papers.

UNC: Moderate coursework. Strong connections to industry. Big program with high student-to-faculty ratio. Students can get "lost" and take a long time to graduate (or not graduate at all).

Michigan: Moderate coursework. Big program. Well-rounded, particularly strong in genetics/genomics and causal inference.

UC Berkeley: Light coursework. High flexibility, "choose your own adventure". Not affiliated with a medical school, so more emphasis on methods than application.

[coffee_7]

This is super helpful! I would love to hear others' opinions on these schools and the next tier(s) down for biostat (specifically looking at Minnesota, Columbia, Penn, Yale, Emory, Brown, Duke, Vanderbilt, BU, Pittsburg). 

[swiftsoc]

On 2/5/2021 at 8:01 AM, coffee_7 said:

This is super helpful! I would love to hear others' opinions on these schools and the next tier(s) down for biostat (specifically looking at Minnesota, Columbia, Penn, Yale, Emory, Brown, Duke, Vanderbilt, BU, Pittsburg). 

Same here! Seems like schools in this tier will be my best option 

[possumvibes]

@coffee_7 I also wonder this! I'd also like to know how top heavy the enrollment numbers are at these top-6 schools relative to the amount of students who attend institutions in the tier directly below. I think (from what I have heard) the departments at all the schools you mentioned are growing relatively quickly and some may breakout to compete with the top schools down the road.

[bio_stat]

On 2/5/2021 at 8:01 AM, coffee_7 said:

This is super helpful! I would love to hear others' opinions on these schools and the next tier(s) down for biostat (specifically looking at Minnesota, Columbia, Penn, Yale, Emory, Brown, Duke, Vanderbilt, BU, Pittsburg). 

very interested to hear about these as well!

[kingduck]

@cyberwulf I am interested to hear about these as well

[AGNSNDN]

Bump! Old post, but definitely worth bringing it back.