Ph.D. in Data Science

Program Overview

Program Details

Degree

Doctor of Philosophy

School

Charles V. Schaefer, Jr. School of Engineering and Science

Department

Computer Science

Available

On campus

Areas of Focus

• Mathematical and statistical modelling including multivariate analytics, financial time series and dynamic programming techniques
• Machine learning and artificial intelligence applications for statistical learning and financial analytics
• Computational systems, exploring advanced algorithm design, distributed systems and cloud technologies
• Data management at scale, involving a deeper dive into data technologies, mobile systems and data management

The Stevens Advantage

• Graduate Cooperative Education Program: Available with two tracks, your co-op experience can serve as a starting point for a research project or augment your on-campus research with complimentary experience.
• International Student Experience: Tap into our expanding worldwide network of research, academic and alumni partners and mentor with our expert faculty in a number of federally-designated STEM degree programs. Optional Practical Training (OPT) or Curricular Practical Training (CPT) is available to gain work experience in your major/field of study.
• State-of-the-Art Research Labs and Facilities: Build, tinker and test your designs in Stevens' MakerCenter, Prototype and Object Fabrication Lab, or numerous other research facilities.
• Research Opportunities: Renowned faculty, labs and research centers – as well as industry partnerships and funding from leading national agencies – support strategic and interdisciplinary research in engineering and science.
• Assistantships and Fellowships: Stevens offers funding to select graduate students in the form of teaching assistantships, research assistantships and fellowships. Limited in number, these highly competitive opportunities are awarded to exceptional candidates based on merit.
• Expanded Learning Options: The Schaefer School offers new opportunities for doctoral students to do coursework at universities in the New York City area – and around the world – through our growing list of academic partnerships with other prestigious universities.

Program Admission Requirements

Who Should Apply?

We welcome applicants with a master’s degree in a technical discipline (such as computer science, business intelligence and analytics, financial analytics, financial engineering or biomedical engineering and chemical biology). However, exceptional applicants with a bachelor’s degree and relevant work experience will also be considered.

Students may begin this Ph.D. program in the fall semester only. Therefore, applications must be submitted by February 1 for admission the following fall. Applicants are generally notified of their admission status around February 15.

Admissions Requirements

• Prerequisite courses in calculus, statistics, probability, algebra and database management
• Fluency in at least one programming language, like C++ or Java
• Transcripts from post-secondary institutions attended
• Two letters of recommendation (academic or professional only; Select Ph.D. programs require a third letter of recommendation)
• Statement of Purpose
• $60 non-refundable Application Fee
• Proof of English language proficiency
• A competitive GRE or GMAT score (required for both part-time and full-time applicants)
• Resume/CV
• Writing sample(s). All applicants are encouraged to submit a lab report (preferable) or paper that they wrote, individually, for an engineering course. Applicants who have published a journal article are also encouraged to submit a copy of their article.

Curriculum Overview

View objectives, outcomes, and other Ph.D. curriculum details in the most recent academic catalog.

Fellowships & Assistantships

Information about assistantships and fellowships can be found here.

STEM Designated Degree Programs

The four fields comprising STEM – science, technology, engineering and mathematics – offer a wide variety of professions that are classified as some of the highest-growing and highest-paying jobs right now and in the future.

A Tech Forward Education

As a Data Science student, you'll work closely with faculty whose research is responsible for important breakthroughs in artificial intelligence, deep learning, computational intelligence and more.

Data Science Faculty

• David Belanger
• Germán Creamer
• Ionut Florescu

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