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What's the difference between these newer computational science PhD programs and PhD programs in the traditional math, physics, cs, and engineering depts?

From checking out a few of these CSE programs online, it seems that they are programs, and not departments, in general, so that the programs have faculty with different home departments.

The interdisciplinary nature of these programs sounds appealing but I wonder if it's better to land up at a traditional engineering dept or a math dept, etc.?

For example, here's some material from Stanford's CSE program:

Ask Big Questions.

Solve Big Problems.

Doctoral Program We develop innovative computational and mathematical approaches for complex engineering and scientific problems, attracting talented PhD students from across the globe. Advised in research by more than 50 faculty from 20-plus departments, PhD students are immersed in a wide variety of fields including statistics and data science, machine and deep learning, control, optimization, numerical analysis, applied mathematics, high-performance computing, earth sciences, flow physics, graphics, bioengineering, genomics, economics and financial mathematics, molecular dynamics, and many more. PhD graduates find outstanding positions in industry and national laboratories as well as in academia.

The last sentence seems that the CSE program is more aimed to prepare their PhD graduates for work in industry, with academic jobs not being the primary goal.

  • Different horses, different courses... – Solar Mike Apr 2 '18 at 12:18
  • with academic jobs not being the primary goal -- This is the norm in engineering, too. – Mad Jack Apr 2 '18 at 12:20
  • "so that the programs have faculty with different home departments": I wouldn't consider this as particularly unusual. We had also programs with faculties belonging to different universities. – Massimo Ortolano Apr 2 '18 at 18:15
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In interdisciplinary research the course works you opt need to be cohesive to help you develop an in depth understanding of the scope and application of the undertaken project.

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With interdisciplinary programs, you gain different skills and may have to prove your skills more if you want to do work that falls into a traditional discipline. You have fewer boundaries and less structure (pro & con). You have more room for creativity and innovation but have to work harder to get your ideas accepted/noticed. You learn a lot of skills translating across different disciplines.

Also, you will not have peers doing the exactly same things you are. You're less likely to fall into comparison traps, because everyone has a separate path, but you are also less likely to have really strong study groups and similar support systems (e.g. ones with the same people across classes and across terms).

Further, it's good you noticed the "programs" vs. "departments" distinction. If most of the people whose first allegiance is to the program are junior and/or adjuncts, then you may have a much tougher time being prepared for academia through this program. If you want to be more competitive for academia, you would want to explicitly build relationships with tenured professors and get a disciplinary Master's degree or certificate (often possible at Stanford on the way to a Ph.D.).

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