Physics with Data Science MPhys 48 months Undergraduate Programme By University of Sussex |TopUniversities
Programme Duration

48 monthsProgramme duration

Tuitionfee

27,300 GBPTuition Fee/year

Starting Month

SepStarting Month

Programme overview

Main Subject

Physics and Astronomy

Degree

MPhys

Study Level

Undergraduate

Study Mode

On Campus

This course combines the power of physics, mathematics and data science to tackle everything from modelling complex physical systems to uncovering patterns in cosmic or experimental data. If you’re keen to study physics but fascinated by data analysis and machine learning, this course is for you.

Technological advancements in physics and data science methods allow us to respond to a wide range of problems. These include modelling disease evolution, mitigating climate change and optimising business models. You’ll study the fundamentals of both subjects and develop the skills to tackle some of the biggest data driven challenges in modern science.

You’ll develop high-level skills in coding, simulation, and statistical analysis, as well as the ability to design and interpret experiments and models. Options enable you to specialise in areas you find most fascinating. They include:
  • quantum mechanics
  • scientific computing
  • electrodynamics
  • data structure and algorithms.

You'll join our friendly, supportive community. In your final year project, you could be working with our expert physicists and data scientists. Our faculty are at the forefront of their fields. Their work includes developing next generation quantum computers, exploring dark energy and quantum effects in black holes, searching for fundamental particles at CERN, and working with NASA’s James Webb Telescope.

By graduation you’ll have gained skills much in demand by employers, including computer programming skills, data analysis and solid research skills. Career options include work in finance, data analytics and software development.

Programme overview

Main Subject

Physics and Astronomy

Degree

MPhys

Study Level

Undergraduate

Study Mode

On Campus

This course combines the power of physics, mathematics and data science to tackle everything from modelling complex physical systems to uncovering patterns in cosmic or experimental data. If you’re keen to study physics but fascinated by data analysis and machine learning, this course is for you.

Technological advancements in physics and data science methods allow us to respond to a wide range of problems. These include modelling disease evolution, mitigating climate change and optimising business models. You’ll study the fundamentals of both subjects and develop the skills to tackle some of the biggest data driven challenges in modern science.

You’ll develop high-level skills in coding, simulation, and statistical analysis, as well as the ability to design and interpret experiments and models. Options enable you to specialise in areas you find most fascinating. They include:
  • quantum mechanics
  • scientific computing
  • electrodynamics
  • data structure and algorithms.

You'll join our friendly, supportive community. In your final year project, you could be working with our expert physicists and data scientists. Our faculty are at the forefront of their fields. Their work includes developing next generation quantum computers, exploring dark energy and quantum effects in black holes, searching for fundamental particles at CERN, and working with NASA’s James Webb Telescope.

By graduation you’ll have gained skills much in demand by employers, including computer programming skills, data analysis and solid research skills. Career options include work in finance, data analytics and software development.

Admission Requirements

6+
3+
59+
169+
80+
34+
1300+
26+
95+
2+

4 Years
Sep

Tuition fees

Domestic
9,535 GBP
International
27,300 GBP

Scholarships

Selecting the right scholarship can be a daunting process. With countless options available, students often find themselves overwhelmed and confused. The decision can be especially stressful for those facing financial constraints or pursuing specific academic or career goals.

To help students navigate this challenging process, we recommend the following articles:

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