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
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:
- Online application for admission (which includes a $60 non-refundable application fee).
- 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.
- 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.
- Two letters of recommendation.
- A resume or curriculum vitae.
International Application Requirements
Chapman’s language of instruction is English. If you have not received a bachelor’s degree (or higher) at an institute where English was the language of instruction, you must demonstrate English proficiency by submitting official scores from an English language exam. You can find additional information here.
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 US 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 US 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 college. (See Academic Policies and Procedures for transfer policies.)
Prerequisites
It is expected that students admitted to the CADS PhD program will have completed substantial preparatory coursework as an undergraduate major or minor from a regionally accredited institution in one of the following disciplines, or the equivalent: Mathematics, Statistics, Computer Science, Data Science, Physics, Electrical Engineering, or Software Engineering. Preparatory coursework must include the following courses, or the equivalent:
- Linear Algebra
- Multivariable Calculus
- Differential Equations
- Computer Programming; Data Structures preferred (R, Python, and SQL)
- Probability and Statistics (Distributions, Confidence Intervals, Hypothesis Testing, Linear Models)
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 a minimum of three members. (See Academic Policies and Procedures .) 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.
Continuous enrollment requirement
Continuous enrollment is required throughout the doctoral program. Students who have not yet successfully defended their dissertation and are not enrolled in any other courses must register for
CS 798A or
CS 798B for a minimum of one credit each term to fulfill the continuous enrollment requirement. The maximum time allowed for completion of the doctoral degree is seven years.
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:
- Minimum grade “B-” or above required in all coursework.
- Maintain 3.000 GPA in the degree.
In order to advance to doctoral candidacy, a student must:
- Pass qualifying examinations on topics from the core courses.
- 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: