- 1.Hakia's analysis of the best machine learning doctoral degree programs reveals that machine learning PhD graduates in industry research earn $150,000 median salary (BLS, 2024), while tenure-track faculty earn $120,000-$180,000.
- 2.Our top-ranked doctoral programs are University of California-Berkeley, University of California-Los Angeles, University of Southern California—selected for research output, funding, and graduate placement.
- 3.Most PhD programs are fully funded: tuition waiver + $25,000-40,000/year stipend. You should not pay for a PhD.
- 4.Average time to degree is 5-6 years, though it varies by research area and advisor.
- 5.60% of machine learning PhD graduates enter industry research (Google, Meta, Microsoft Research); 40% pursue academic careers.
Source: A machine learning PhD is worth it if you want to conduct original research, whether in academia or industry research labs. Unlike master's programs, PhDs are typically fully funded (tuition + ~$35K/year stipend). Industry research scientists at Google, Meta, and OpenAI earn $200K-400K+. Academic faculty earn less but enjoy research freedom and job security.
Why Pursue a Machine Learning PhD?
A PhD is the terminal research degree in machine learning—required for tenure-track faculty positions and highly valued for industry research scientist roles. According to the Bureau of Labor Statistics, Computer and Information Research Scientists with advanced degrees can earn $208,000+ or more, especially in research-focused positions.
Who Should Consider a PhD?
- Aspiring academics: Tenure-track faculty positions require a PhD
- Research scientists: Industry labs (Google Research, Microsoft Research, Meta AI) recruit PhDs for cutting-edge research
- Deep specialists: Those who want to push the boundaries of machine learning
- Intellectually curious: People who find fulfillment in solving hard, unsolved problems
The PhD Value Proposition
- Fully funded: No tuition + $25K-45K/year stipend (you're paid to learn)
- Research freedom: Work on problems that interest you with expert guidance
- Career options: Both academic ($100K-200K faculty) and lucrative industry paths ($150K-400K+ research scientist)
- Expertise: Become a world expert in machine learning
Important: Don't pursue a PhD just for salary gains. If your goal is maximizing income quickly, a master's + industry experience often yields better short-term returns. A PhD is a 5-6 year commitment to research mastery.
Best Machine Learning PhD Programs - Top 10
University of California-Berkeley
Berkeley's ML research merges statistics with computational sciences. BAIR Lab and ML@B student organization lead ML community. Ranked #3 in US engineering schools.
University of California-Berkeley Machine Learning & Data Science Program Overview
Hakia ranks University of California-Berkeley as the #1 in machine learning & data science degree program.
University of California-Berkeley's Machine Learning & Data Science program graduates 57 students annually with a 96% graduation rate. San Francisco Bay Area
Hakia Insight: University of California-Berkeley leverages partnerships with Google and Meta to offer students real-world project experience valued by employers.
Degree Programs
Research Labs & Institutes
Location Advantages
- •San Francisco Bay Area
- •Silicon Valley ML hub
Industry Partners
Career Outcomes
Google, OpenAI, Meta AI
Certifications & Designations
Admissions
University of California-Los Angeles
UCLA ranks #7 in Machine Learning (CSrankings.org). Strong causal inference research tradition from Judea Pearl.
University of California-Los Angeles Machine Learning & Data Science Program Overview
Hakia ranks University of California-Los Angeles as the #2 in machine learning & data science degree program.
University of California-Los Angeles's Machine Learning & Data Science program graduates 37 students annually with a 92% graduation rate. Located in Los Angeles tech hub
Hakia Insight: University of California-Los Angeles's direct partnerships with Google and Amazon give students a competitive edge through industry-embedded projects and recruiting pipelines.
Degree Programs
Research Labs & Institutes
autonomous systems
specialized computing
sensor networks
cybersecurity
health technology
Location Advantages
- •Located in Los Angeles tech hub
- •Access to major cloud computing companies
- •Strong industry connections in Southern California
Industry Partners
Career Outcomes
Google, Amazon, Meta
Admissions
University of Southern California
USC features Information Sciences Institute and Institute for Creative Technologies for ML research. ORAI is first AI+OR interdisciplinary PhD globally.
University of Southern California Machine Learning & Data Science Program Overview
Hakia ranks University of Southern California as the #3 in machine learning & data science degree program.
University of Southern California's Machine Learning & Data Science program graduates 59 students annually with a 92% graduation rate. Los Angeles tech hub
Hakia Insight: Students at University of Southern California benefit from active collaborations with Amazon and Meta, connecting classroom learning to the workforce.
Degree Programs
Research Labs & Institutes
Location Advantages
- •Los Angeles tech hub
- •Entertainment industry ML
Industry Partners
Career Outcomes
Google, Amazon, Defense contractors
Admissions
University of California-Irvine
UCI's ICS is the largest doctoral program on campus (250+ students). 5-year funding guarantee with strong ML research.
University of California-Irvine Machine Learning & Data Science Program Overview
Hakia ranks University of California-Irvine as the #4 in machine learning & data science degree program.
University of California-Irvine's Machine Learning & Data Science program graduates 28 students annually with a 96% graduation rate. Orange County tech corridor
Hakia Insight: University of California-Irvine's industry network — including Google and Amazon — provides students with internship and hiring pathways.
Degree Programs
Research Labs & Institutes
Location Advantages
- •Orange County tech corridor
- •Gaming industry ML
Industry Partners
Career Outcomes
Google, Amazon, Gaming companies
Admissions
University of California-San Diego
UCSD houses Terry Sejnowski (founding father of AI) and $220M NSF-funded TILOS Institute.
University of California-San Diego Machine Learning & Data Science Program Overview
Hakia ranks University of California-San Diego as the #5 in machine learning & data science degree program.
University of California-San Diego's Machine Learning & Data Science program graduates 38 students annually with a 81% graduation rate. San Diego biotech corridor
Hakia Insight: Through ties with Qualcomm and Google, University of California-San Diego bridges the gap between academic training and industry practice.
Degree Programs
Research Labs & Institutes
Location Advantages
- •San Diego biotech corridor
- •Qualcomm headquarters
Industry Partners
Career Outcomes
Qualcomm, Google, Biotech companies
Admissions
University of California-Santa Barbara
UCSB hosts inaugural Agentic AI Summit (Jan 2026). Strong AI for Science research integrating ML with physics.
University of California-Santa Barbara Machine Learning & Data Science Program Overview
Hakia ranks University of California-Santa Barbara as the #6 in machine learning & data science degree program.
University of California-Santa Barbara's Machine Learning & Data Science program graduates 30 students annually with a 90% graduation rate. Santa Barbara research environment
Hakia Insight: Students at University of California-Santa Barbara benefit from active collaborations with Google and Amazon, connecting classroom learning to the workforce.
Degree Programs
Research Labs & Institutes
AI ethics, fairness, bias, privacy, transparency
quantitative finance and probabilistic methods
statistical data science
computational methods
Location Advantages
- •Santa Barbara research environment
- •CA tech corridor access
Industry Partners
Career Outcomes
Google, Amazon, Tech startups
Admissions
Columbia University in the City of New York
Columbia's ML research is led by David Blei. Amazon partnership for AI Technology Center. Full 5-year PhD funding.
Columbia University in the City of New York Machine Learning & Data Science Program Overview
Hakia ranks Columbia University in the City of New York as the #7 in machine learning & data science degree program.
Columbia University in the City of New York's Machine Learning & Data Science program graduates 37 students annually with a 100% graduation rate. Access to New York Academy of Sciences Machine Learning Symposium
Hakia Insight: Through ties with Amazon and Google NYC, Columbia University in the City of New York bridges the gap between academic training and industry practice.
Degree Programs
Research Labs & Institutes
Causal inference and AI
General machine learning research
Quantitative imaging biomarkers for cancer screening, prognosis, and treatment
AI/ML methods for multi-organ, multi-omics data in human aging and disease
Medical image acquisition technique improvement using physics and engineering
Advanced neuroimaging, data analysis, and machine learning for clinical practice
Ultrasound-based imaging and therapy tools for brain, heart, vessels, and nerves
Location Advantages
- •Access to New York Academy of Sciences Machine Learning Symposium
- •Integration with NYC tech ecosystem
- •Proximity to medical and healthcare institutions for biomedical AI applications
Industry Partners
Career Outcomes
Google, Meta, Finance companies
Admissions
Stanford University
Stanford ML Group leads cutting-edge ML research. CS229 is foundational ML course. Fei-Fei Li (TIME 2025 Person of Year) co-directs HAI.
Stanford University Machine Learning & Data Science Program Overview
Hakia ranks Stanford University as the #8 in machine learning & data science degree program.
Stanford University offers comprehensive Machine Learning & Data Science programs at multiple degree levels, combining rigorous academics with practical experience. Heart of Silicon Valley
Hakia Insight: Stanford University's direct partnerships with Google and Apple give students a competitive edge through industry-embedded projects and recruiting pipelines.
Degree Programs
Research Labs & Institutes
Location Advantages
- •Heart of Silicon Valley
- •OpenAI and Google proximity
Industry Partners
Career Outcomes
Admissions
California Institute of Technology
California Institute of Technology is a private institution with strong machine learning doctoral research programs.
California Institute of Technology Machine Learning & Data Science Program Overview
Hakia ranks California Institute of Technology as the #9 in machine learning & data science degree program.
California Institute of Technology's Machine Learning & Data Science program graduates 9 students annually with a 88% graduation rate. Pasadena, CA location
Hakia Insight: California Institute of Technology graduates earn $180,000, driven by the program's industry connections and hands-on machine learning & data science curriculum.
Degree Programs
Research Labs & Institutes
Autonomous systems and robotics AI
Mathematical foundations of ML
Theoretical computer science and ML theory
Neuroscience and brain-inspired computing
Location Advantages
- •Pasadena, CA location
Industry Partners
Career Outcomes
Google, Apple, Microsoft, Meta, Amazon
Certifications & Designations
Admissions
Cornell University
Cornell AI Initiative since early 1990s. Dual-campus (Ithaca + Cornell Tech NYC) provides research and industry access.
Cornell University Machine Learning & Data Science Program Overview
Hakia ranks Cornell University as the #10 in machine learning & data science degree program.
Cornell University's Machine Learning & Data Science program graduates 38 students annually with a 95% graduation rate. Ithaca campus + Cornell Tech NYC
Hakia Insight: Students at Cornell University benefit from active collaborations with Google and Microsoft, connecting classroom learning to the workforce.
Degree Programs
Research Labs & Institutes
AI research
data science and modeling
human-computer interaction
cybersecurity and privacy
Location Advantages
- •Ithaca campus + Cornell Tech NYC
- •Access to NYC tech ecosystem
Industry Partners
Career Outcomes
Google, Microsoft, NYC tech companies
Admissions
Best Machine Learning PhD Programs - Top 10 — Complete Program Data
#1. University of California-Berkeley Machine Learning & Data Science Program
Hakia ranks University of California-Berkeley as the #1 in machine learning & data science degree program. Location: Berkeley, CA | Type: Public | Tuition: $11,834/year | Graduation Rate: 96% | Score: 100.0
What makes University of California-Berkeley stand out: Berkeley's ML research merges statistics with computational sciences. BAIR Lab and ML@B student organization lead ML community. Ranked #3 in US engineering schools.
Hakia Insight: University of California-Berkeley leverages partnerships with Google and Meta to offer students real-world project experience valued by employers.
Program Overview: UC Berkeley offers ML research through EECS and Statistics PhD programs. Machine Learning at Berkeley (ML@B) is a student-run organization fostering ML community. Statistical machine learning merges statistics with computational sciences for large-scale data problems. Stuart Russell was elected to NAE 2025, Song Mei received a Sloan Fellowship 2025.
Degree Programs: Ph.D. in EECS (ML Focus) (5-6 years); Ph.D. in Statistics (Statistical ML) (5 years)
Research Labs: BAIR Lab; Machine Learning at Berkeley (ML@B); Statistical ML Research
Industry Partners: Google, Meta, OpenAI, NVIDIA, Tech startups
Career Outcomes: | Top Employers: Google, OpenAI, Meta AI
Notable Faculty: Gabriel Gomes (Mechanical Engineering and Transportation Studies); Joshua Hug (Electrical Engineering and Computer Sciences); Reed Walker (Business and Public Policy and Economics); Jonathan Kolstad (Economic Analysis and Policy)
Admissions: GPA: 3.0+
Accreditations: WASC-accredited
#2. University of California-Los Angeles Machine Learning & Data Science Program
Hakia ranks University of California-Los Angeles as the #2 in machine learning & data science degree program. Location: Los Angeles, CA | Type: Public | Tuition: $11,834/year | Graduation Rate: 92% | Score: 98.4
What makes University of California-Los Angeles stand out: UCLA ranks #7 in Machine Learning (CSrankings.org). Strong causal inference research tradition from Judea Pearl.
Hakia Insight: University of California-Los Angeles's direct partnerships with Google and Amazon give students a competitive edge through industry-embedded projects and recruiting pipelines.
Program Overview: UCLA offers ML research through Computer Science and Statistics & Data Science PhD programs. Research labs include Machine Intelligence (MINT) group and Automated Reasoning Group. UCLA is ranked #7 in Machine Learning on CSrankings.org. Strong connections to Judea Pearl's causal inference work.
Degree Programs: Master of Science (M.S.); Doctor of Philosophy (Ph.D.); Master of Engineering - Artificial Intelligence
Research Labs: Autonomous intelligent networks and systems center - autonomous systems; Domain-specific computing center - specialized computing; Embedded networked sensing center - sensor networks; Information security center - cybersecurity; Wireless health center - health technology
Industry Partners: Google, Amazon, Meta, Microsoft
Career Outcomes: | Top Employers: Google, Amazon, Meta
Notable Faculty: Prof. Guy Van den Broeck (Artificial Intelligence - Area Director); Prof. K. Chang (Natural Language Processing); Prof. A. Darwiche (Automated Reasoning); Prof. V. Roychowdhury (Large-Scale Data Mining and Complex Networks)
Admissions: GPA: 3.75 average admitted
#3. University of Southern California Machine Learning & Data Science Program
Hakia ranks University of Southern California as the #3 in machine learning & data science degree program. Location: Los Angeles, CA | Type: Private | Tuition: $66,640/year | Graduation Rate: 92% | Score: 96.5
What makes University of Southern California stand out: USC features Information Sciences Institute and Institute for Creative Technologies for ML research. ORAI is first AI+OR interdisciplinary PhD globally.
Hakia Insight: Students at University of Southern California benefit from active collaborations with Amazon and Meta, connecting classroom learning to the workforce.
Program Overview: USC offers ML doctoral research through Computer Science and Marshall's Data Sciences & Operations PhD programs. The Information Sciences Institute and Institute for Creative Technologies provide advanced ML research opportunities. New ORAI program combines AI and Operations Research.
Degree Programs: MS in Computer Science (Artificial Intelligence) (2-3 semesters); MS in Electrical Engineering (Machine Learning and Data Science) (2-3 semesters)
Research Labs: Information Sciences Institute; Institute for Creative Technologies; ORAI Program
Industry Partners: Amazon, Meta, Capital One, Boeing, Intel, Google, Apple, Microsoft, Uber, Qualcomm
Career Outcomes: | Top Employers: Google, Amazon, Defense contractors
Notable Faculty: Leaders in NLP and affective computing; Strong defense research
Admissions: GPA: Competitive
#4. University of California-Irvine Machine Learning & Data Science Program
Hakia ranks University of California-Irvine as the #4 in machine learning & data science degree program. Location: Irvine, CA | Type: Public | Tuition: $11,834/year | Graduation Rate: 96% | Score: 94.4
What makes University of California-Irvine stand out: UCI's ICS is the largest doctoral program on campus (250+ students). 5-year funding guarantee with strong ML research.
Hakia Insight: University of California-Irvine's industry network — including Google and Amazon — provides students with internship and hiring pathways.
Program Overview: UC Irvine's ICS offers ML research within Computer Science and Statistics PhD programs. The largest doctoral program on campus with 250+ students. Research spans machine learning, pattern recognition, and data mining. 5-year funding guarantee for PhD students.
Degree Programs: BS (4 years); MS; PhD
Research Labs: Machine Learning Lab; Data Mining Research; Pattern Recognition Group
Industry Partners: Google, Amazon, Microsoft, Gaming companies
Career Outcomes: | Top Employers: Google, Amazon, Gaming companies
Notable Faculty: Leaders in ML and data mining; Strong industry connections
Admissions: GPA: 3.5 for PhD
#5. University of California-San Diego Machine Learning & Data Science Program
Hakia ranks University of California-San Diego as the #5 in machine learning & data science degree program. Location: La Jolla, CA | Type: Public | Tuition: $11,834/year | Graduation Rate: 81% | Score: 93.5
What makes University of California-San Diego stand out: UCSD houses Terry Sejnowski (founding father of AI) and $220M NSF-funded TILOS Institute.
Hakia Insight: Through ties with Qualcomm and Google, University of California-San Diego bridges the gap between academic training and industry practice.
Program Overview: UCSD offers ML research through CSE PhD and Halıcıoğlu Data Science Institute PhD. Terry Sejnowski (founding father of AI) and Rose Yu (ML for climate/healthcare) lead research. $220M NSF-funded TILOS Institute for Learning-enabled Optimization at Scale.
Degree Programs: Specialized Certificate in Machine Learning Methods (12 months); B.S. in Cognitive Science with Machine Learning and Neural Computation Specialization (4 years)
Research Labs: TILOS Institute; Halıcıoğlu Data Science Institute; MLsys@UCSD
Industry Partners: Qualcomm, Google, Amazon, Biotech companies
Career Outcomes: | Top Employers: Qualcomm, Google, Biotech companies
Notable Faculty: Dr. Virginia de Sa (computational modeling, psychophysics studies, machine learning for visual and multi-sensory perception); Dr. Zhuowen Tu (computer vision, machine learning, deep learning, neural computation, neuro imaging); Dr. Bradley Voytek (oscillatory network communication, automated science, data-mining, cognitive brain-computer interfaces); Dr. Eran Mukamel (computational analysis of large-scale neural data, electrophysiology, computational epigenomics)
Admissions: GPA: Competitive
#6. University of California-Santa Barbara Machine Learning & Data Science Program
Hakia ranks University of California-Santa Barbara as the #6 in machine learning & data science degree program. Location: Santa Barbara, CA | Type: Public | Tuition: $11,834/year | Graduation Rate: 90% | Score: 93.2
What makes University of California-Santa Barbara stand out: UCSB hosts inaugural Agentic AI Summit (Jan 2026). Strong AI for Science research integrating ML with physics.
Hakia Insight: Students at University of California-Santa Barbara benefit from active collaborations with Google and Amazon, connecting classroom learning to the workforce.
Program Overview: UC Santa Barbara offers ML research within Computer Science PhD. 'AI for Science' course develops unified frameworks integrating ML with physics-based constraints. Inaugural Agentic AI Summit January 2026. Strong computational science applications.
Degree Programs: MS in Computer Science (2 years); PhD in Computer Science (4-6 years); PhD in Statistics and Applied Probability; BS/MS Combined Computer Science
Research Labs: Center for Responsible Machine Learning - AI ethics, fairness, bias, privacy, transparency; Center for Financial Mathematics and Actuarial Research - quantitative finance and probabilistic methods; Data Science Initiative - statistical data science; Center for Scientific Computing at California NanoSystems Institute - computational methods
Industry Partners: Google, Amazon, Tech startups
Career Outcomes: | Top Employers: Google, Amazon, Tech startups
Notable Faculty: Xin (Eric) Wang - computer use agents; Leaders in applied ML
Admissions: GPA: 3.5+ typical
#7. Columbia University in the City of New York Machine Learning & Data Science Program
Hakia ranks Columbia University in the City of New York as the #7 in machine learning & data science degree program. Location: New York, NY | Type: Private | Tuition: $64,526/year | Graduation Rate: 100% | Score: 92.9
What makes Columbia University in the City of New York stand out: Columbia's ML research is led by David Blei. Amazon partnership for AI Technology Center. Full 5-year PhD funding.
Hakia Insight: Through ties with Amazon and Google NYC, Columbia University in the City of New York bridges the gap between academic training and industry practice.
Program Overview: Columbia offers ML research through Computer Science PhD with Data Science option. The Data Science Institute and Center of AI Technology (Amazon partnership) provide research opportunities. Professor David Blei leads ML research. Full 5-year funding with tuition and stipend.
Degree Programs: Ph.D. in Computer Science (ML) (5-6 years)
Research Labs: Causal Artificial Intelligence Lab - Causal inference and AI; Machine Learning @ Columbia - General machine learning research; Computational Imaging Biomarker Group (CBIG) - Quantitative imaging biomarkers for cancer screening, prognosis, and treatment; Laboratory of AI and Biomedical Science (LABS) - AI/ML methods for multi-organ, multi-omics data in human aging and disease; Medical Imaging and Physics Lab - Medical image acquisition technique improvement using physics and engineering; Payabvash Lab - Advanced neuroimaging, data analysis, and machine learning for clinical practice; Ultrasound and Elasticity Imaging Laboratory - Ultrasound-based imaging and therapy tools for brain, heart, vessels, and nerves
Industry Partners: Amazon, Google NYC, Meta NYC, Finance companies
Career Outcomes: | Top Employers: Google, Meta, Finance companies
Notable Faculty: Dr. David Blei (Machine learning and probabilistic modeling); Dr. Elias Bareinboim (Causal inference); Dr. Daniel Hsu (Statistical machine learning); Dr. Carl Vondrick (Computer vision); Dr. Shih-Fu Chang (Computer vision and multimedia); Dr. Alexandr Andoni (Machine learning algorithms); Dr. Toniann Pitassi (Computational complexity and machine learning theory); Dr. Adam Block (Machine learning theory); Dr. Yunzhu Li (Robotics and machine learning); Dr. Nakul Verma (Machine learning theory)
Admissions: GPA: Very competitive
#8. Stanford University Machine Learning & Data Science Program
Hakia ranks Stanford University as the #8 in machine learning & data science degree program. Location: Stanford, CA | Type: Private | Tuition: $61,731/year | Score: 92.5
What makes Stanford University stand out: Stanford ML Group leads cutting-edge ML research. CS229 is foundational ML course. Fei-Fei Li (TIME 2025 Person of Year) co-directs HAI.
Hakia Insight: Stanford University's direct partnerships with Google and Apple give students a competitive edge through industry-embedded projects and recruiting pipelines.
Program Overview: Stanford's CS PhD offers world-leading ML research through Stanford ML Group and HAI. First-year students rotate in three labs before selecting advisor. CS229 (Machine Learning) is foundational course. 5-6 year completion typical with lab rotations.
Degree Programs: Machine Learning Specialization (3 courses, self-paced); Artificial Intelligence Graduate Certificate (1-4 courses depending on selection); PhD in Computer Science (5-6 years); MS in Computer Science (1-2 years)
Research Labs: Stanford ML Group; Stanford AI Lab (SAIL); Stanford HAI
Industry Partners: Google, Apple, Meta, OpenAI, Stanford startups
Career Outcomes:
Notable Faculty: Andrew Ng (Machine Learning and Artificial Intelligence); Christopher Manning (Natural Language Processing); Chelsea Finn (Deep Learning and Meta Learning); Percy Liang (Machine Learning and Natural Language Processing); Jeanette Bohg (Robotics)
Admissions: GPA: 3.0 minimum
#9. California Institute of Technology Machine Learning & Data Science Program
Hakia ranks California Institute of Technology as the #9 in machine learning & data science degree program. Location: Pasadena, CA | Type: Private | Tuition: $60,816/year | Graduation Rate: 88% | Score: 92.5
What makes California Institute of Technology stand out: California Institute of Technology is a private institution with strong machine learning doctoral research programs.
Hakia Insight: California Institute of Technology graduates earn $180,000, driven by the program's industry connections and hands-on machine learning & data science curriculum.
Program Overview: California Institute of Technology offers a doctoral program in machine learning designed for students pursuing advanced research and academic careers. Located in Pasadena, CA, the program emphasizes original research contributions, dissertation work, and preparation for leadership roles in academia and industry.
Degree Programs: Ph.D. in Machine Learning (4-6 years); Direct Ph.D. Track (5-7 years)
Research Labs: Center for Autonomous Systems and Technologies - Autonomous systems and robotics AI; Dolciani Mathematical Center - Mathematical foundations of ML; Information Science and Technology - Theoretical computer science and ML theory; Tianqiao and Chrissy Chen Institute - Neuroscience and brain-inspired computing
Industry Partners: Google, Amazon, Microsoft Research, JPL/NASA, NVIDIA
Career Outcomes: | Top Employers: Google, Apple, Microsoft, Meta, Amazon, Tesla, JPL, Top research institutions | Common Roles: Machine Learning Engineer, Research Scientist, AI Researcher, Data Scientist, Principal Software Engineer
Admissions: GPA: 3.5+ recommended
Accreditations: Research publications, Conference presentations, Industry research internships
#10. Cornell University Machine Learning & Data Science Program
Hakia ranks Cornell University as the #10 in machine learning & data science degree program. Location: Ithaca, NY | Type: Private | Tuition: $65,204/year | Graduation Rate: 95% | Score: 91.4
What makes Cornell University stand out: Cornell AI Initiative since early 1990s. Dual-campus (Ithaca + Cornell Tech NYC) provides research and industry access.
Hakia Insight: Students at Cornell University benefit from active collaborations with Google and Microsoft, connecting classroom learning to the workforce.
Program Overview: Cornell's CS PhD offers ML research through AI concentration. Cornell AI Initiative approaches AI with curiosity, conscience, and collaboration. Dual-campus presence (Ithaca + Cornell Tech NYC). Research spans NLP, computer vision, and ML theory.
Degree Programs: Certificate in Applied Machine Learning and AI (4 months); Master of Engineering in Data Science and Decision Analytics; Master of Engineering in Computer Science; Master of Engineering in Computer Science; Jacobs Technion-Cornell Dual MS Degrees (2 years); PhD
Research Labs: Artificial Intelligence - AI research; Data & Modeling - data science and modeling; Human-Centered Computing - human-computer interaction; Security & Privacy - cybersecurity and privacy
Industry Partners: Google, Microsoft, Amazon, NYC tech companies
Career Outcomes: | Top Employers: Google, Microsoft, NYC tech companies
Notable Faculty: Leaders in NLP and ML theory; Strong interdisciplinary connections
Admissions: GPA: Competitive
Full Machine Learning Doctoral Rankings 2026
| Rank | |||||
|---|---|---|---|---|---|
| 1 | University of California-Berkeley | Berkeley, CA | Public | 96% | 100 |
| 2 | University of California-Los Angeles | Los Angeles, CA | Public | 92% | 98.4 |
| 3 | University of Southern California | Los Angeles, CA | Private | 92% | 96.5 |
| 4 | University of California-Irvine | Irvine, CA | Public | 96% | 94.4 |
| 5 | University of California-San Diego | La Jolla, CA | Public | 81% | 93.5 |
| 6 | University of California-Santa Barbara | Santa Barbara, CA | Public | 90% | 93.2 |
| 7 | Columbia University in the City of New York | New York, NY | Private | 100% | 92.9 |
| 8 | Stanford University | Stanford, CA | Private | — | 92.5 |
| 9 | California Institute of Technology | Pasadena, CA | Private | 88% | 92.5 |
| 10 | Cornell University | Ithaca, NY | Private | 95% | 91.4 |
| 11 | Princeton University | Princeton, NJ | Private | 96% | 90.4 |
| 12 | University of California-Davis | Davis, CA | Public | 91% | 90.1 |
| 13 | University of Washington-Seattle Campus | Seattle, WA | Public | 97% | 89.5 |
| 14 | Massachusetts Institute of Technology | Cambridge, MA | Private | — | 87.8 |
| 15 | Carnegie Mellon University | Pittsburgh, PA | Private | 98% | 86.9 |
| 16 | Stony Brook University | Stony Brook, NY | Public | 89% | 86 |
| 17 | Harvard University | Cambridge, MA | Private | — | 85.4 |
| 18 | Tufts University | Medford, MA | Private | 81% | 84.6 |
| 19 | University of Maryland-College Park | College Park, MD | Public | 84% | 84.5 |
| 20 | Northwestern University | Evanston, IL | Private | 90% | 84.2 |
| 21 | University of California-Santa Cruz | Santa Cruz, CA | Public | 93% | 84.1 |
| 22 | Brown University | Providence, RI | Private | 96% | 83.8 |
| 23 | University of California-Riverside | Riverside, CA | Public | 83% | 83.8 |
| 24 | University of North Carolina at Chapel Hill | Chapel Hill, NC | Public | 93% | 83.4 |
| 25 | Rice University | Houston, TX | Private | 93% | 83.4 |
Showing 1–25 of 50
Research Areas & Specializations
PhD programs in machine learning offer multiple specialization tracks. Your research area determines your advisor options, publication venues, and career trajectories.
Key Machine Learning Research Areas
- Deep Learning
- Reinforcement Learning
- Computer Vision
- Natural Language Processing
- Generative Models
Emerging Research Topics (2024-2025)
- Foundation Models
- Learning Theory
- Optimization
- Generative AI
- Safe and Aligned ML
Choosing Your Specialization: Your research area should align with your interests, available advisors, and career goals. Review faculty research pages and recent publications. Attend seminars and read papers from top venues in machine learning to understand current research directions.
Publication Venues: Check CSRankings.org to see which conferences and journals are most prestigious for your chosen specialization. Top-tier venues vary significantly by subfield.
Finding the Right Advisor
Your advisor is the single most important factor in PhD success. A good advisor shapes your research trajectory, opens networking opportunities, and directly impacts your career outcomes. According to data from NSF's Survey of Earned Doctorates, advisor-student fit is strongly correlated with time to degree and completion rates.
What to Look For in an Advisor:
- Research alignment: Their work should genuinely excite you—you'll spend 5+ years on related problems
- Advising style: Some are hands-on, others hands-off. Know what you need and ask current students
- Funding stability: Do they have ongoing grants? Have they consistently funded students?
- Student outcomes: Where did their graduates end up? Academia? Industry? How long did they take?
- Lab culture: Talk to current students privately about work-life balance and lab dynamics
Red Flags to Avoid:
- High student turnover or many students leaving without degrees
- Faculty who are rarely available or traveling constantly
- Labs where students seem stressed, isolated, or unhappy
- Advisors with a history of conflicts or complaints
Pro tip: Email 2-3 current students and ask: "What do you wish you knew before joining this lab?" Their candid responses will tell you more than any faculty website.
PhD Funding & Stipends
You should not pay for a PhD.
Top programs offer full funding packages covering tuition plus a competitive stipend. According to CSStipendRankings.org and PhDStipends.com, computer science stipends range from $18,000 at lower-paying programs to $50,000+ at top institutions.
2024-25 Stipend Examples:
- Brown University: $49,000/year ($4,084/month) - Graduate School
- Duke University: Full funding for 5 years including tuition, fees, insurance, and stipend - CS Department
- Emory University: $37,467/year for CS/Informatics PhDs - Graduate School
- Mid-tier programs: Typically $25,000-35,000/year with full tuition waiver
Funding Sources:
- Research Assistantships (RA): Work on faculty research; most common funding source
- Teaching Assistantships (TA): Lead discussion sections, grade assignments
- Fellowships: Competitive awards (NSF GRFP, NDSEG, university fellowships) with higher stipends and research freedom
- Grants: Faculty research grants often fund PhD students
Cost of Living Warning: Use PhDStipends.com to compare living wage ratios, which normalize stipends to local cost of living. A $35K stipend in a low-cost city may provide better quality of life than $50K in San Francisco.
PhD Milestones & Timeline
The NSF Survey of Earned Doctorates tracks time to degree across all fields. Computer science PhDs typically take 5-6 years to complete, though this varies by research area and institution.
Typical PhD Timeline:
- Years 1-2: Coursework, rotations (if applicable), identify research area, pass qualifying exams
- Years 2-3: Thesis proposal, begin independent research, first publications
- Years 3-5: Core research, conference publications, build professional network
- Years 5-6: Complete dissertation, defend, job market
Key Milestones:
- Qualifying Exam: Usually year 1-2; tests breadth of knowledge and/or research potential
- Thesis Proposal: Year 2-3; defines your dissertation scope and convinces committee it's viable
- Candidacy: After proposal passes; you're now "ABD" (All But Dissertation)
- Dissertation Defense: Final oral exam presenting your complete research
What affects time to degree: Research area complexity, advisor expectations, publication requirements, whether you switch topics, and how quickly you identify a viable research direction.
Application Process
PhD admissions are highly competitive. According to ProFellow, top programs accept 5-15% of applicants. The process differs significantly from undergraduate or master's admissions.
Typical Application Components:
- Statement of Purpose: Your research interests, why this program, and potential advisors (2-3 pages)
- Letters of Recommendation: 3 letters, ideally from research supervisors who know your work deeply
- CV/Resume: Emphasize research experience, publications, and technical projects
- GRE Scores: Many programs have made GRE optional since 2020; check requirements
- Transcripts: Strong grades help, but research experience often matters more
- Research samples: Some programs request writing samples or research proposals
Timeline:
- September-November: Research programs, contact potential advisors, prepare materials
- December 1-15: Most application deadlines
- January-March: Interview invitations (virtual or in-person visit days)
- March-April 15: Admission decisions; April 15 is the standard decision deadline
Critical tip: Reach out to potential advisors before applying. A brief, professional email expressing genuine interest in their research can significantly improve your chances—especially if they respond positively and mention your application to the admissions committee.
Industry Research vs Academic Faculty Careers
| Factor | Industry Research | Academic Faculty |
|---|---|---|
| Starting Salary | $150,000-$200,000+ | $100,000-$140,000 |
| Salary Ceiling | $300,000-$500,000+ (with equity) | $150,000-$250,000 |
| Job Security | Project-dependent, at-will | Tenure after 6-7 years |
| Research Freedom | Aligned with company goals | High autonomy after tenure |
| Publication Pressure | Varies by company | Essential for tenure |
| Resources | Well-funded, large compute | Grant-dependent |
| Work-Life Balance | Generally better | Highly variable |
| Impact Timeline | Faster deployment | Long-term influence |
| Typical Employers | Google, Meta, Microsoft, OpenAI | Universities, research institutes |
Source: Salary data from [CRA Taulbee Survey](https://cra.org/resources/taulbee-survey/) and [Glassdoor](https://www.glassdoor.com/Salaries/)
Choosing Your Career Path
Industry research is right for you if:
- Compensation is a priority
- You want to see research deployed at scale
- You prefer shorter feedback loops
- You're comfortable with more directed research agendas
- Geographic flexibility is important (industry hubs)
Academia is right for you if:
- Research freedom is paramount
- You want to mentor the next generation
- Job security matters more than peak compensation
- You enjoy teaching
- You want to pursue long-term, speculative research
Increasingly blurred lines: Many researchers move between academia and industry. Some professors consult extensively; some industry researchers teach courses. The choice isn't permanent.
Postdoc Pathways
A postdoc is a temporary research position after completing your PhD. According to Academic Positions, postdoc salaries average $61,000-$72,000 in 2024, with most positions lasting 2-3 years.
When is a Postdoc Necessary?
- Academic careers: Often expected, especially at research universities. Strengthens your publication record and expands your network.
- Industry careers: Rarely necessary—most industry research labs hire directly from PhD programs
- Switching fields: A postdoc can help you pivot to a new research area
- Building independence: Develops skills in grant writing, lab management, and independent research
Postdoc Considerations:
- Duration: 1-3 years typical; longer postdocs can signal difficulty finding permanent positions
- Salary gap: Postdocs earn significantly less than industry PhDs—factor this into your decision
- Location flexibility: Postdocs often require relocation; be prepared to move
- Exit strategy: Have a clear plan for what comes after the postdoc
Important: In computer science, a postdoc is increasingly optional. Strong PhD graduates with good publication records can go directly to tenure-track positions or industry research roles.
Publication Expectations
Publications are the currency of academic research. In computer science, conference papers (not journals) are the primary publication venue, unlike most other fields.
Typical Publication Expectations:
- Minimum for graduation: 2-4 peer-reviewed publications (varies by program and advisor)
- Competitive job market: 5+ publications with at least 1-2 at top-tier venues
- Top-tier venues: NeurIPS, ICML, CVPR, ACL, SIGCOMM, SOSP, PLDI (varies by subfield)
- First-author papers: Critical for demonstrating independent research ability
Publication Timeline:
- Year 1-2: Workshop papers, co-authored papers with senior students
- Year 3-4: First-author publications at good venues
- Year 5+: Aim for top venues, build a coherent research narrative for job market
Quality vs Quantity: One strong paper at a top venue (NeurIPS, ICML, etc.) often matters more than several papers at lower-tier venues. Focus on impactful work that others will cite and build upon.
Resources: Check CSRankings.org to understand which venues matter most in your subfield and how faculty are evaluated by publication record.
Top States for Machine Learning Doctoral Programs
| State | Total Programs | Median Tuition | Top Program |
|---|---|---|---|
| Best Machine Learning Doctoral Programs in California | 25 | $9,500 | University of California |
| Best Machine Learning Doctoral Programs in Texas | 20 | $8,500 | University of Texas |
| Best Machine Learning Doctoral Programs in New York | 18 | $12,000 | SUNY |
| Best Machine Learning Doctoral Programs in Florida | 15 | $6,500 | University of Florida |
| Best Machine Learning Doctoral Programs in Virginia | 12 | $11,000 | Virginia Tech |
| Best Machine Learning Doctoral Programs in Pennsylvania | 14 | $14,000 | Penn State |
Machine Learning & AI Career Track
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Machine Learning PhD Frequently Asked Questions
Data Sources
Federal database of U.S. postsecondary institutions
Computer science research publication rankings by faculty
May 2024 salary data for research positions
Related Machine Learning Resources
Taylor Rupe
Co-founder & Editor (B.S. Computer Science, Oregon State • B.A. Psychology, University of Washington)
Taylor combines technical expertise in computer science with a deep understanding of human behavior and learning. His dual background drives Hakia's mission: leveraging technology to build authoritative educational resources that help people make better decisions about their academic and career paths.