University of Cambridge
University of Cambridge

MPhil in Data Intensive Science

The MPhil in Data Intensive Science at the University of Cambridge offers an unparalleled opportunity to delve into cutting-edge research at the intersection of big data and fundamental science. Leveraging Cambridge's world-leading academic reputation, students gain access to state-of-the-art facilities and collaborate with renowned experts in astrophysics, particle physics, and computational methods. This program is ideal for those seeking to apply advanced data science techniques to some of humanity's most profound scientific questions, fostering a unique blend of theoretical depth and practical application.

science STEM Designated
schedule Duration

36 Months

school Level

Masters

location_on Location

United Kingdom

stars Credits

180

menu_book Syllabus & Modules

01

Statistical Inference

Core Module

02

Machine Learning for Scientific Data

Core Module

03

Big Data Technologies

Core Module

04

Astrophysical Data Analysis

Core Module

05

Particle Physics Data Analysis

Core Module

06

Scientific Computing

Core Module

07

Bayesian Methods in Data Science

Core Module

08

Data Visualisation

Core Module

Career Outcomes

Employment Rate

Graduates employed within 6 months

90%
Employed
Other

Average Starting Salary

£45,000 - £75,000

Core Focus & Roles

Data Scientist Machine Learning Engineer Research Scientist Quantitative Analyst
Graduates are highly sought after in academia (PhD research), technology companies (data scientist, machine learning engineer), financial services (quantitative analyst), and scientific research institutions. They are equipped to tackle complex data challenges across various industries, contributing to innovation and discovery.

Entry Requirements

language

English & Others

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Accepts 15 Years Education

Yes

GMAT N/A
GRE N/A
SAT N/A
ACT N/A
IELTS 7
TOEFL 100
PTE N/A
Duolingo N/A
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MAX. Backlogs Allowed

4

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Application Fee

85

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Deposit Fee

Yes

event

Document Submission Deadline

Fall:- Jan 14

event

Application Deadline

Fall:- Jan 14

Apply for this Course open_in_new Official Course open_in_new
event

Scholarship Deadline

Fall :- Jan 7

school

Academic

  • Min GPA 85
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