Difference between Computational Science and Engineering (CSE) doctoral degrees and traditional math, physics, cs, engineering and biology degrees 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.
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.