PhD in Statistics

Class Profile

Class Size

25

Average Age

27

Average Work Experience

2 Years

Diversity

Others:

1%

Two or more races:

3%

White:

49%

Hispanic or Latino:

10%

Black or African American:

10%

Asian:

27%

Career Outcomes

Median Earnings After Graduation

$1,10,000 / year

Top recruiters

Accenture

Deloitte

KPMG

Google

Cisco

Apple

Cisco Systems

Facebook

Dell

HP

BHP

Tesla

Dell Technologies

Fees and Funding

Tuition Fees

$16,058 / year

FAQs

• What are the key research areas and features of the program?
  
  Research in computational statistics and machine learning at Georgia Tech is broad, including: Computer vision, robotics, deep learning, natural language processing, data analysis, optimization, AI, computational finance, high-performance computing, and more. The curriculum is designed to provide strong foundational knowledge and advanced techniques for interdisciplinary applications in science, engineering, and business. Students select courses and research specializations from multiple academic units, with faculty and resources spanning nine schools across three colleges.
• What documentation is required for the application?
  
  Official academic transcripts from all institutions attended Curriculum Vitae (CV) Statement of purpose/research interests Three letters of recommendation Proof of English proficiency (TOEFL, IELTS), if applicable Additional materials (e.g., writing sample, GRE scores) may be required by specific home units or faculty supervisors.
• How do I apply for the PhD in Computational Statistics and Machine Learning at Georgia Tech?
  
  Review research areas and identify potential faculty supervisors in the relevant programs. Prepare application materials: academic transcripts, CV, statement of purpose, proof of English proficiency (if needed), and letters of recommendation. Applications are submitted online through the Georgia Tech Graduate Admissions portal. Most PhD programs have annual application deadlines in December or January for entry the following fall.
• What are the minimum academic and English language entry requirements?
  
  Candidates need a strong background in mathematics, statistics, computing, or engineering. Applicants should hold a Bachelor’s or Master’s degree in a relevant field. Non-native English speakers must submit proof of proficiency (TOEFL or IELTS), with requirements set by the Graduate School. Additional prerequisites may include prior coursework in statistics, linear algebra, and advanced calculus.
• What is the structure and duration of the PhD in Computational Statistics and Machine Learning at Georgia Tech?
  
  Georgia Tech offers an interdisciplinary PhD in Machine Learning and a closely related PhD in Computational Science and Engineering (CSE), both highly relevant for advanced research in statistics, data science, and machine learning. The PhD in Machine Learning is a collaborative program between the Colleges of Computing, Engineering, and Sciences, with students typically completing the degree in approximately five years of full-time study. The curriculum features core and elective coursework, a qualifying examination, and a dissertation based on original research.