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Admission Snapshot
Typical admitted student: A master's degree in a related field such as computer science, mathematics, statistics, or engineering is typically required, along with a minimum GPA of 3.0 and strong research or quantitative background. GRE scores are often required or recommended, particularly for competitive programs.
About This Program
A pioneering doctoral program focused on developing researchers who can translate methodological innovations in data science and AI into practical applications across various domains.
Career Outcomes
Pursue advanced AI Research Scientist in Cross-Industry AI through natural language processing
- 1. Data Science Researcher
- 2. AI Research Scientist
- 3. Machine Learning Engineer
- 4. Chief Data Officer
What You'll Learn
- Design and implement advanced AI models for complex data problems
- Conduct original research in machine learning and data-driven discovery
- Analyze large-scale datasets using statistical and computational methods
- Develop scalable AI systems with high-performance computing techniques
Curriculum Highlights
The program requires 72 credits, featuring core courses in machine learning and big data, research rotations, and a final dissertation on an original research topic.
Top Employers
Top employers include Google, Microsoft, Amazon, Meta, and research institutions like IBM Research and national labs.
Admissions
A master's degree in a related field such as computer science, mathematics, statistics, or engineering is typically required, along with a minimum GPA of 3.0 and strong research or quantitative background. GRE scores are often required or recommended, particularly for competitive programs.
Application Materials
- Statement of Purpose: Required
- Letters of Recommendation: 3
- Resume: Required
- Transcripts: Official transcripts required
Academic Requirements
- Degree Required: Master's degree
- GRE/GMAT: Required or Optional
- TOEFL/IELTS: Required for international students (TOEFL 80+ / IELTS 6.5+)
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