Chances at computational science grad schools

In summary: I would go with Purdue. Purdue has a pretty good program too, so it's not like I'm sacrificing anything.In summary, the main area of interest the applicant has is computational fluid dynamics. They have a BS in physics and applied math and are interested in pursuing a PhD. They have research experience in solid-state physics and two internships in industry. They have strong GRE scores and good academic credentials. They are considering four schools for their PhD program: Texas-Austin, MIT, Stanford, and U of Texas at Austin.
  • #1
creepypasta13
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0
I'm about to apply to grad programs in AE/ME and computational science right now. I have a general interest in doing numerical and computational work on physical problems. So that's why I'm considering computational science but not applied math programs. For now, the main area of interest I have is computational fluid dynamics.

I got my BS degrees in physics and applied math last year. I ultimately want to do research in my career, so I'm pretty sure I want the phD, but I'm not 100% sure

GRE: 800Q, 470V, 5.0 W. I may have to take the GRE math subject as a lot of the computational science programs recommend but don't require it
GPA: 3.77 overall and major. But I only took 2 engineering courses: A in heat transfer and B- in fluid mechanics.
Research experience: An REU in solid-state physics, and 2 quarters of research with an applied math prof doing research in materials modeling. No publications
Work experience: Two different internships in industry, including one that just ended last week

LORs: One from REU prof. Another from the prof I did research with in math (but he's a post-doc). My guess is that these LORs will be good but not great. I've heard various opinions for who to choose for my last LOR. I could choose a physics prof I took a class with 3 years ago, my heat transfer prof I got an A with 6 months ago (but he also works at a company, so he might not even have a phD), or my two different hiring managers at my internships (one has a phD in applied math in CFD)

Because I plan on applying to 4-8 grad schools in AE/ME also, I've only listed these schools as possible choices for computational science programs:

texas-austin, MIT, stanford (website says RAship only given to MS students with firm commitment to pHd - does that mean chances are really slim?), maryland, minnesota

I would appreciate any comments. Thanks
 
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  • #2
I would maybe suggest applying to more schools. MIT, Stanford, and U of Texas at Austin (especially the first two) are extremely hard to get into even for the most qualified applicants. I don't know anything about Maryland and Minnesota, but I would assume they are less competitive. Maybe add some more schools of that sort.
 
  • #3
so Texas-Austin isn't within my reach? Anyways, there just aren't many programs in computational science, so the only other school I've seen that's in the same range as Maryland and Minnesota is Purdue. Unless someone here can suggest other schools within my reach
 

Related to Chances at computational science grad schools

1. What is computational science?

Computational science is a multidisciplinary field that combines computer science, mathematics, and scientific disciplines to solve complex problems through computational methods and simulations.

2. What are the requirements for admission to a computational science graduate program?

The specific requirements may vary between programs, but most commonly, applicants are expected to have a strong background in mathematics and computer science, as well as relevant coursework and research experience in their chosen field of study.

3. What is the job outlook for graduates of computational science programs?

The job outlook for graduates of computational science programs is very promising. With the increasing use of technology and data in various industries, there is a high demand for professionals with strong computational skills. Graduates can pursue careers in industries such as healthcare, finance, and technology, as well as in research and academia.

4. What factors should I consider when choosing a computational science graduate program?

When choosing a computational science graduate program, it is important to consider factors such as the program's curriculum, faculty expertise, research opportunities, and industry connections. It is also important to consider the location, cost, and overall fit of the program for your academic and career goals.

5. Are there any specialized areas within computational science that I can focus on?

Yes, there are many specialized areas within computational science, including computational biology, computational finance, computational physics, and computational chemistry. It is important to research and choose a program that aligns with your interests and career goals.

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