Southern Methodist University Fully Funded PhD in Data Science

PhD @Southern Methodist University posted 1 week ago

Job Description

Southern Methodist University (SMU) in Dallas, Texas, offers a fully funded Ph.D. program in Data Science through its Department of Statistics and Data Science. This interdisciplinary program is a collaborative effort among SMU’s Dedman College of Humanities and Sciences, Cox School of Business, and Lyle School of Engineering, providing students with a comprehensive education that bridges multiple disciplines.

Program Overview

  • Degree: Ph.D. in Data Science

  • Duration: Typically 4–5 years

  • Credit Hours: 60 total (48 coursework + 12 dissertation)

  • Core Curriculum: Courses in Computer Science, Statistics, and Data Science

  • Electives: Options in Mathematics, Finance, Marketing, Education, Psychology, Chemistry, Game Design, Economics, and more

  • Research Rotations: Two summer research rotations after the first and second years

  • Professional Activities: Participation in seminars, conferences, and publication requirements

Funding and Financial Support

All admitted Ph.D. students receive comprehensive financial support, which includes:​

  • Tuition Remission: Full coverage of tuition fees

  • Stipend: Competitive annual stipend through teaching and research assistantships

  • Health Insurance: University-subsidized health insurance coverage

Additional funding opportunities may be available through fellowships such as the Moody and Mustang Fellowships, which offer $30,000 per year, and the NSF Research Training Group (RTG) fellowships, providing at least $30,000 per year for up to three years.

Admission Requirements

  • Educational Background: An undergraduate or master’s degree in an engineering or mathematical field. Applicants with degrees in other fields may qualify if they have completed:

    • Three semesters of calculus (through multivariate calculus)

    • One semester each of linear algebra and computer programming (or equivalent experience)

  • GRE: Optional

  • English Proficiency: TOEFL scores required for international applicants from non-English-speaking countries, unless they have earned a degree from an English-language institution in specified countries

Unique Features

  • Interdisciplinary Approach: The program’s structure allows students to engage with multiple disciplines, reflecting the broad applicability of data science.

  • Research Rotations: Students participate in research projects across different departments, enhancing collaborative and communication skills.

  • Professional Development: Requirements include attending seminars, presenting research at conferences, and publishing in academic venues.

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