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1

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Massachusetts Institute of Technology

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Massachusetts

United States

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Program Rank

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1

The PhD in Physics, Statistics and Data Science at the prestigious Massachusetts Institute of Technology (MIT) is designed for those aspiring to excel in the interdisciplinary domains of data science, statistical analysis, and physics. This immersive program is anchored in both theoretical knowledge and practical application, preparing graduates to tackle complex problems across various fields, including academia, industry, and research. The curriculum is thoughtfully structured to integrate advanced statistical techniques with essential principles of physics, fostering a comprehensive understanding of data-driven science. With a strong emphasis on research, students are encouraged to develop innovative methodologies that contribute to the evolving landscape of data science and physics.
This program's curriculum is characterized by a rigorous selection of courses that cover a spectrum of topics essential to mastering the fields of statistics and data science. Core courses include Statistical Methods, Machine Learning, Data Mining, and Advanced Topics in Physics. Additionally, students can choose elective courses that delve into specialized areas like Biostatistics, Computational Physics, and Statistical Computing. The program spans a duration of approximately 60 months, allowing ample time for both coursework and research initiatives. The integration of theoretical studies with hands-on projects enables students to gain practical experience and apply their learning in real-world scenarios.
At MIT, students benefit from the expertise of a distinguished faculty, composed of leading researchers and practitioners in the fields of physics and data science. The faculty adopts a unique teaching methodology that promotes interaction, collaboration, and critical thinking. Faculty members often serve as mentors, guiding students through their research journey and helping them refine their ideas into impactful projects. The close-knit academic environment fosters a vibrant exchange of ideas, encouraging students to question, innovate, and engage with complex concepts in data science and physics.
Research opportunities at MIT are robust, with access to cutting-edge labs and facilities. Students have the chance to engage in groundbreaking research initiatives that can shape the future of technology and scientific discovery. The university promotes interdisciplinary collaboration, allowing students to work alongside peers from various disciplines, leading to diverse perspectives and enhanced problem-solving capabilities. Additionally, students can take advantage of numerous resources, including research centers focused on data science, statistics, and physics, which provide critical support for their academic endeavors.
The program also emphasizes the importance of industry connections and internship possibilities. MIT's strong ties with leading companies and organizations provide students with invaluable opportunities to gain practical experience and enhance their professional network. These internships often lead to job placements upon graduation, with alumni successfully entering high-demand fields such as statistical programming, biostatistics, and educational consultancy. With a median base salary of around $110,000, graduates can expect a rewarding career path, underpinned by a high graduation rate of 96%.
Moreover, the program boasts a rich history of alumni success stories, showcasing the potential career pathways available to graduates. Many have gone on to hold prestigious positions within top universities, research institutions, and industry leaders, effectively contributing to advancements in physics and data science. Alumni often return to share their experiences and insights, further enriching the educational environment for current students.
As a unique feature of the program, MIT emphasizes international diversity, with 31.1% of students representing various countries and cultures. This diverse environment not only enhances the learning experience but also prepares students to work in a globalized workforce.
**Why Study PhD in Physics, Statistics and Data Science at MIT?**

  • World-renowned faculty with expertise in both theoretical and practical domains.
  • A comprehensive curriculum that integrates physics with advanced statistical methods.
  • Robust research opportunities in cutting-edge facilities and labs.
  • Strong industry connections leading to high-quality internships and job placements.
  • A vibrant academic community with a high retention rate and strong alumni network.
  • Opportunities to engage in interdisciplinary collaboration across various departments.
  • Support for international students, promoting a diverse and inclusive learning environment.

To be eligible for this esteemed program, applicants are required to submit various documents, including transcripts, a statement of purpose, a resume, and letters of recommendation (both academic and professional). Additionally, international students must demonstrate proficiency in English, typically through an IELTS score of at least 7.0, with no individual band lower than 7.0. Although the GRE requirement is currently unknown, candidates are encouraged to check for any updates regarding standardized testing requirements. The application fee is set at $90, and students must adhere to the deadlines, with the next deadline being December 15th, 2024, for the Fall intake.
Overall, the PhD in Physics, Statistics and Data Science at MIT is more than just an academic program; it is a comprehensive platform that prepares students to become leaders in their respective fields. With a combination of rigorous coursework, faculty mentorship, and extensive research opportunities, graduates are well-equipped to navigate and impact the evolving landscape of data science and physics.
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Total Tuition Fees

$3,00,000

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Duration

60 Months

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Median Salary

$1,10,000

Ranking

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#2

US World and News Report

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#5

The World University Rankings

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#1

QS World University Rankings

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Intake

Fall ( Sept - Nov )

Class Profile

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Class Size

25

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Average Age

30

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Average Work Experience

3 Years

Diversity

Black or African American:

12%

Others:

8%

Two or more races:

5%

Asian:

15%

Hispanic or Latino:

12%

White:

48%

Career Outcomes

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Median Earnings After Graduation

$1,10,000 / year

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Graduation Rate

96%

Prospective Job Roles

Statistician

Biostatistician

Physics Teacher

Physics Education Instructor

Physics Education Consultant

Physics Education Writer

Physics Education Software Developer

Physics Education Program Manager

Physics Education Policymaker

High School Physics Teacher

Medical Statistician

Pharmaceutical Statistician

Statistical Programmer

Cancer Statistician

Physics Education Researcher

Physics Education Technology Developer

Physics Education Policy Analyst

College Physics Professor

Top recruiters

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Eligibility Criteria

English Proficiency Tests

  • TOEFL

    90

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  • IELTS

    7

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Application Requirements

Here's everything you need to know to ensure a complete and competitive application—covering the key documents and criteria for a successful submission.

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Application Fee: 90

  • intake

    Transcript

  • intake

    Passport

  • intake

    Statement of Purpose

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    Resume

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    IELTS

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    Academic LOR

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    Professional LOR

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    Professional LOR

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    Essay

Application Deadlines

Standard Deadline
FallDec 15, 2024

Fees and Funding

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Tuition Fees

$60,000 / year

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Overall Cost

$75,000 / year

FAQs

  • Yes, this is possible for the “computation and statistics” and “data analysis” requirements, with permission of program co-chairs. Substitutions for the “probability” and “statistics” requirements will only be granted in exceptional cases. For Spring 2021, the following course has been approved as a substitution for the “computation and statistics” requirement: 18.408 (Theoretical Foundations for Deep Learning). The following course has been approved as a substitution for the “data analysis” requirement: 6.481 (Introduction to Statistical Data Analysis).

  • These courses are required by all of the IDPS degrees. They are meant to ensure that all students obtaining an IDPS degree share the same solid grounding in these fundamentals, and to help build a community of IDPS students across the various disciplines. Only in exceptional cases might it be possible to substitute more advanced courses in these areas.

  • Yes, this is possible, as long as the courses are already on the approved list of requirements. E.g. 8.592 can count as a breadth requirement for a NUPAX student as well as a Data Analysis requirement for the PhysSDS degree

  • Harvard CompSci 181 will count as the equivalent of MIT’s 6.867. For the status of other courses, please contact the program co-chairs.

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