Ph.D. in Data Science

The Ph.D. program goes beyond the academic dimension and prepares candidates to solve real-world problems using data science methods in areas of academia, government labs or offices, data-centric companies, entrepreneurial startup companies, or wherever data science experts are called upon to meet the increasing demands of an expanding global ecosystem.

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(Qualifying students may be eligible for an application fee waiver. Contact Dr. Hai Phan, program director, at phan@njit.edu for further information.)

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The Ph.D. in Data Science is jointly administered by the Department of Data Science in the Ying Wu College of Computing and the Department of Mathematical Sciences in the College of Science and Liberal Arts. To accommodate different interest profiles of students, the program offers two options. There is significant overlap between the two options.

Computing Option

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Statistics Option

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Students graduating with a PhD degree in Data Science should anticipate the acquisition of skills, knowledge, and professional training that will enable them to pursue data science careers such as data scientist, data analyst, data engineer, data miner, and academic data science researcher in a broad range of industrial sectors, startups, academia, and government institutions. The primary goal of the PhD degree in Data Science is to educate students who have the necessary skills and knowledge to pursue competitive professional and academic careers, swiftly advancing to leadership positions and to contribute to the creation of novel insights and knowledge in the field.

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Application deadlines are October 15 for spring and December 15 for fall. However, we will continue to accept applications after the deadline for qualified candidates. Prospective applicants are expected to have software development experience, computational skills, and an understanding of statistical methods. The minimum requirements for admission to the PhD program are within the guidelines and policies approved by the University and include:
  1. A Bachelor’s degree in data science, computer science, informatics, mathematics/statistics, engineering, or another closely related discipline (as approved by the PhD directors) from a college or university accredited in the United States, or its equivalent, with an expected overall GPA of 3.5 out of 4.0.
  2. GRE scores are required. They will be evaluated in agreement with other Ph.D. programs at NJIT.
  3. Prepared students shall have a good background in programming and data structures (corresponding to NJIT CS 280 and CS 435), multivariate calculus (e.g. NJIT Math 211), and Probability and Statistics (e.g. Math 333/341). Admitted students lacking competencies in one or more of these areas shall consult with the academic advisor to take relevant preparatory courses. 
  4. International student applicants shall demonstrate proficiency in English if it is not their first language, following the NJIT admission standard. Exemptions can be granted to applicants who have earned (or will earn, before enrolling at NJIT) a Bachelor’s, Master’s, or Doctoral degree from a university of recognized standing in a country in which all instruction is provided in English.
To continue in the Ph.D. program, a student must fulfill the following requirements/milestones:
  • Maintain a cumulative GPA of 3.0 or better. Students will need a cumulative GPA of 3.5 if they wish to be considered for financial support of any kind.
  • End of year one: Students must take the written part of the Ph.D. qualifying exam.
    • Every student (in both options) will have to pass qualifying exams in these two courses:  
      • CS 675     Machine Learning
      • MATH 644    Regression
    • Students in the Computing option will also have to pass:
      • CS 644   Introduction to Big Data OR   IS 650   Data Visualization & Interpretation
    • Students in the Statistics option will also have to pass:
      • MATH 631    Linear Algebra
Upon the approval of the PhD program director, students must file a program of study that lists the courses to be taken and the timeline of study. 
Students are recommended to choose a dissertation advisor as soon as possible, but no later than 3 months after passing the qualifying exam. A student needs to inquire who among the tenured/tenure track faculty is closest to their area of research interest. The Ph.D. program director should be consulted for this purpose, unless the student has already determined who they wish to work with, e.g., based on class offerings or publication records.  Students will have to pass the oral part of the qualifying exam, followed by registering for research credits. They have to present, orally and in writing, a Dissertation Proposal and, before graduating, have to write and orally defend a state-of-the-art research dissertation in front of a committee of faculty members.  Individual professors will impose publication requirements in conferences and/or academic journals as a condition for graduating. 

 

“Data is the new oil. Like oil, data is valuable, but if unrefined it cannot really be used. It has to be changed into gas, plastic, chemicals, etc. to create a valuable entity that drives profitable activity. So must data be broken down, analyzed for it to have value.” - The British mathematician Clive Humbly