I'm deciding between Berkeley statistics and Harvard biostatistics for a PhD. I've been working as a biostatistician for three years, and want to focus on the more methodological areas of biostatistics. I'm not sure what I want to do after graduating, but want to stay in research.
Berkeley statistics offers a more theoretical program, but has relatively few faculty (~5) working on biostatistics. Moreover, those in biostatistics seem to be focusing on single cell data recently. But, the work is more methodological, and there is still some applied work being done. On the upside, Berkeley has no quals and the students seem nice. It seems like recent graduates are split between good positions in academia and tech companies.
Harvard biostatistics is big, and there are a lot of faculty working on a ton of different things. The department isn't all applied, and seems to have a bit of methodological work (including some Bayesian stuff). There're also many hospitals in the area and the department has a ton of high quality data. It seems like recent graduates end up post-doc-ing a bit, or going to biostatistical research institutes, but that post-docs from Harvard tend to get good positions in academia.
My SO might be able to transfer his job to the Bay area, which is an advantage, as is the better weather. Cost of living isn't that different between both places. Harvard is ranked #1 for biostatistics, and Berkeley #2 for statistics (though note that Berkeley biostatistics is #6, and the biostatistics and statistics faculty overlap).
Is anyone familiar with the programs, or with the more intangible factors from both departments (e.g., culture)? I welcome any thoughts that anyone has!