Dec 15, 2019  
2019-2020 Graduate Catalog 
    
2019-2020 Graduate Catalog

Computational and Data Sciences, Ph.D.


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The Ph.D. in Computational and Data Sciences is a 70 credit post baccalaureate research degree. The curriculum places strong emphasis on each student's background with the goal of producing high-quality doctoral research.

Computational scientists construct mathematical models, develop quantitative analysis techniques and use modern computing technology to tackle big data problems in a wide variety of disciplines. Some aspects of computational science, such as machine learning and predictive analytics, have become identified as the new field of data science. Computational and data scientists tackle fundamental scientific, engineering and business problems through the use of advanced computing methodologies.

Computational and data scientists work in and across a wide variety of disciplines by applying high-performance computing to fuse data sets, visualize theoretical possibilities and create knowledge. The goal is to engage cutting-edge technology to answer the most perplexing scientific questions.

Admission to the program and prerequisites

An undergraduate degree specifically in computational science is not required for admission. The program will consider applicants from a broad range of undergraduate and master's level science disciplines (e.g. biology, chemistry, computer science, biochemistry, cell and molecular biology, mathematics, physics). Admission will depend on the relationship between the student's goals and the program's objectives as well as the likelihood that the student will benefit from the program.

Admission to the program may be achieved by the completion of the following requirements:

  1. Online application for admission (which includes a $60 non-refundable application fee).
  2. Official transcripts from degree conferring institution(s) including all post-baccalaureate graduate coursework and advanced degree (if applicable). A cumulative grade point average of 3.000 is required.
  3. Graduate Record Examination (GRE) - general test scores are required and must have been taken within the last five years. Applicants must achieve the following minimum scores: Verbal 153, Quantitative 146, Analytical Writing 4.0.
  4. Statement of intent - a 750 word essay. Applicants are expected to address science topics they are interested in and how they envision applying computational science in those areas.
  5. Two letters of recommendation.
  6. A resume or curriculum vitae.

International Application Requirements

Language Test
Because our programs are taught completely in English and the classroom experience will require a strong understanding of the English language, we require all our students to have strong English language skills. Chapman does not have an ESL program for international students on campus - international students who are non-native English speakers need to demonstrate English proficiency at the time of admission.

Applicants who have completed their degree (Bachelor and Graduate) at an institution where English was not the primary language of instruction must submit minimum scores from one of the following English language exams:

  • Test of English as a Foreign Language (TOEFL): 600 (PBT) or 100 (iBT) (Institution Code: 4047)
  • International English Language Testing System (IELTS): 7.0
  • Pearson Test of English (PTE Academic): 68
  • Cambridge English Advanced Exam (CAE): Level C1

Exam scores must come directly from the testing agency to Chapman University and have been taken within two years of the date of application.

Official Transcripts and Diploma

  • Your application requires official transcripts in both the native language, and in English. If your university does not provide translations of your transcript, you will need to have your transcript translated, line-by-line and word-for-word exactly. You will need to submit both the official transcript and the official translation.
  • If your university only provides one official transcript, you will need to submit a notarized copy. You will need to take your official transcript and have certified copies made, and translated into English if needed. These documents should be stamped by the legal notary who made the copy and/or translation. We do not accept uncertified copies directly from students. Please note that official documents will be required upon acceptance.
  • While your diploma will not be required with your application, your enrollment into Chapman University will be dependent upon submission of your official diploma. Should you be admitted, your diploma will need to be submitted in both the native language, and in English. You will need to submit both the official diploma and the official translation. If your university only provides one official diploma, you may send a notarized copy, or bring the original documents into our office at the time classes begin.

GPA Evaluation
Once your transcripts are received, Chapman University will conduct an in-house evaluation of your credentials to determine your U.S. equivalent GPA.

Supplemental Application

  • The International Supplemental Application is the financial certification form that provides comprehensive information about your passport, I-20 requirements, and financial support for your studies. This form is required for F-1 student visa applicants.
  • Should you be admitted into our program, you will be sent information on how to access the Supplemental Application.
  • If you hold a U.S. passport, or are a permanent resident, you do not need to submit this document. You will apply as a domestic student.

Current M.S. Students

Computational and Data Sciences M.S. students who wish to enroll in the Ph.D. program need to pass the Ph.D. qualifying exams prior to being admitted.

Transfer policy

Students admitted to the Ph.D. in Computational and Data Sciences degree program may transfer up to 18 credits completed toward graduate degree coursework upon approval by the program director and the dean of the school. (See Academic Policies and Procedures  for transfer policies.)

Continuous enrollment requirement

Continuous enrollment is required throughout the Ph.D. program. See Continuous Enrollment  for additional information. The maximum time allowed for completion of the Ph.D. is seven years.

Prerequisites

Equivalent preparation (or foundation courses) may be used to satisfy the following requirements:

  1. Differential Equations
  2. Computer Programming; Data Structures preferred
  3. Probability and Statistics

Foundation courses

For admitted students who have verified potential, but require supplementary support for success in the CADS program. Most students are expected to waive these courses. 

Requirements for the Ph.D. in Computational and Data Sciences degree

The degree consists of core courses, elective courses, research courses and dissertation comprising a total of 70 credits and is structured as follows:

  • Core courses (13 credits): These courses provide a common foundation for conducting research in computational science.
  • Elective and research credits (45 credits, with a minimum of 15 credits at the 700 level): Elective credits provide deeper investigations into areas of application for computational science. Research credits are more specialized credits and are extremely personalized, matching the specific research topics of interest to students and faculty.
  • Dissertation research credits (12 credits): These are credits for work on the doctoral dissertation.

During the third semester of the program each student will work with the faculty to create a Doctoral Committee consisting of three faculty members. Either one faculty member will serve as the chair of the Doctoral Committee or two faculty members will serve as co-chairs. The student, together with the Doctoral Committee, will prepare an academic plan for the student that will specify the remaining elective courses and the doctoral research courses that the student will take and will also specify the problem or area of research that the student will explore in the student's dissertation. The academic plan will be submitted to the Doctoral Steering Committee and must be approved by the Doctoral Steering Committee before the student can continue to the third year.

Students pursuing the Ph.D. in Computational and Data Sciences are held to the University's Academic Policies and Procedures . In addition these specific degree standards apply:

  • Completion of prerequisite or foundation courses.
  • Minimum grade "C+" or above required in all coursework.
  • Maintain 3.000 GPA in the degree.
  • In order to advance to doctoral candidacy, a student must:
  1. Pass qualifying examinations on topics from the core courses.
  2. Pass a preliminary oral examination on topics from elective and research courses selected by the student's Doctoral Committee.

The following courses make up the Ph.D. in Computational and Data Sciences curriculum:

core courses (13 credits)


These courses provide a common foundation for conducting research in computational science.

elective and research courses (45 credits)


Courses selected from among the graduate courses in computational sciences including biology, earth sciences, computer science, mathematics, physics and economic sciences. A minimum of 15 credits must be at the 700 level. CS 797 - Dissertation Research , courses do not count towards elective credits.

dissertation courses (12 credits)


total credits 70


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