Program Overview
This four-year integrated Master's program in Physics with Data Analytics and Machine Learning prepares students for data-driven challenges in modern science. Combining physics with data science topics and advanced research skills, graduates are equipped for careers in finance, data analytics, software development, and research. The program emphasizes versatile, transferable skills, fostering success in industry or academia.
Program Outline
Degree Overview:
This integrated Masters course is designed for students interested in advanced physics and data analysis and machine learning. It aims to equip students with the knowledge and skills to tackle data-driven challenges in modern science. The program covers topics in physics and data science, including quantum mechanics, scientific computing, electrodynamics, and data structure and algorithms. Students will work with a departmental research group headed by expert physicists and data scientists, gaining advanced skills in programming, data analysis, and research.
Outline:
- Duration: 4 years full time
- Typical A-level offer: AAA
- UCAS code: F3G7
- Start date: September 2025
Year 1:
- Autumn teaching:
- Foundations of Data Analysis
- Introduction to Astrophysics
- Mathematical Methods for Physics 1
- Mechanics and Heat
- Physics Study Success
- Spring teaching:
- Data Structures & Algorithms
- Mathematical Methods for Physics 2
- Physics Year 1 Laboratory
- Waves, Fields and Modern Physics
Year 2:
- Autumn teaching:
- Electrodynamics
- Mathematical Methods for Physics 3
- Physics Year 2 Laboratory
- Scientific Computing
- Spring teaching:
- Applied Machine Learning
- Applying Physics Skills
- Quantum Mechanics 1
- Thermal and Statistical Physics
Year 3:
- Autumn teaching:
- Advanced Physics Laboratory A
- Atomic Physics
- Condensed State Physics
- Linear Statistical Models (L6)
- Spring teaching:
- Advanced Physics Laboratory B
- Quantum Mechanics 2
- Statistical Inference (L.6)
Year 4:
- Autumn teaching:
- Algorithmic Data Science
- Atom Light Interactions
- Cosmology
- Data Analysis Techniques
- Data Science Research Methods
- Galactic Astrophysics
- General Relativity
- Quantum Computing
- Quantum Field Theory
- Symmetry and the Standard Model
- Spring teaching:
- Advanced Cosmology
- Advanced Natural Language Processing
- Astrophysical Processes
- Beyond the Standard Model
- Electrons, Cold Atoms & Quantum Circuits
- Frontiers in Particle Physics
- Image Processing
- Introduction to Nano-materials and Nano-characterisation
- Machine Learning
- Monte Carlo Simulations (L7)
- Particle Physics Detector Technology
- Practical Quantum Technologies
- Wider Topics in Data Science (L7)
- Autumn and spring teaching:
- MPhys Final Year Project
Teaching:
- The department is a friendly, close-knit community.
- The department is a core part of the SEPnet (South East Physics Network) consortium, which gives them links to universities and industries across the region.
Careers:
- Career options include work in finance, data analytics, software development, and research, at university or in industry.
- Students will develop versatile and transferable skills, preparing them for jobs in industry or academia.
- Potential graduate jobs include:
- Data scientist or data analyst
- Software engineer
- Investment analyst
- Financial trader
- Game designer
- CAD technician
- Teacher
Other:
- The program is also offered as a three-year BSc without the integrated Masters year.
- Students can apply for eight-week funded summer placements through SEPnet’s Employer Programme.
- The department offers a wide range of paid work opportunities within the department, including teaching and research opportunities in the summer, and outreach roles throughout the year.
