Physics with Data Science MSci

Program Overview

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The Physics with Data Science MSci at the University of Birmingham combines a strong physics foundation with data science expertise. Students gain skills in physics fundamentals, data science algorithms, and techniques, preparing them for careers in academia, industry, and finance. The program is accredited by the Institute of Physics and features a year-long research project, personalized tutorials, and access to state-of-the-art facilities.

Program Outline

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Degree Overview:

The Physics with Data Science MSci program at the University of Birmingham is a four-year Masters of Science degree that provides a strong foundation in both physics and data science. The program is co-taught with the School of Computer Science and aims to equip students with the skills and expertise needed to excel in careers that require both physics and data science knowledge. The program's objectives include:

• Providing a broad understanding of the fundamentals of physics, including classical mechanics, quantum mechanics, electromagnetism, optics, and more.
• Building data science knowledge through mathematical and computational modules, specialized modules, and projects.
• Developing experience and expertise in data science techniques, algorithms, and processes.

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Outline:

The Physics with Data Science MSci program is structured over four years, with a focus on core modules in the first two years and a wider range of optional modules in the later years.

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Year 1:

• Core Modules:
• Classical Mechanics and Relativity 1 (10 credits)
• Classical Mechanics and Relativity 2 (10 credits)
• Electromagnetism and Temperature and Matter (20 credits)
• Introduction to Data Science (10 credits)
• Introduction to Probability and Statistics (10 credits)
• Mathematics for Physicists 1A (10 credits)
• Mathematics for Physicists 1B (10 credits)
• Physics Laboratory 1A (10 credits)
• Physics Laboratory 1B (10 credits)
• Physics and Communication Skills 1 (10 credits)
• Quantum Mechanics and Optics and Waves (10 credits)

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Year 2:

• Core Modules:
• Data Science Projects (10 credits)
• Electromagnetism 2 (10 credits)
• Foundations and Applications of Data Science (10 credits)
• Mathematics for Physicists 2A (10 credits)
• Mathematics for Physicists 2B (10 credits)
• Optics (10 credits)
• Particles and Nuclei & A Quantum Approach to Solids (10 credits)
• Physics and Communication Skills 2 (10 credits)
• Physics Laboratory 2 (10 credits)
• Quantum Mechanics 2 (10 credits)
• Statistical Physics and Entropy (10 credits)
• Optional Modules:
• Choose 10 credits from a selection including:
• Eigenphysics (10 credits)
• Electronics (10 credits)
• Lagrangian and Hamiltonian Mechanics (10 credits)
• Observational Astronomy (10 credits)
• Structure in the Universe (10 credits)

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Year 3:

• Core Modules:
• General Physics (10 credits)
• Group Studies (20 credits)
• Quantum Mechanics 3 (10 credits)
• Scientific Computing Laboratory 1 (10 credits)
• Scientific Computing Laboratory 2 (10 credits)
• Statistical Physics (10 credits)
• Optional Modules:
• Choose 50 credits (20 credits in semester 1 and 30 credits in semester 2) from a selection including:
• Semester 1:
• Biophysics (10 credits)
• Complex Variable Theory (10 credits)
• Fission and Fusion (10 credits)
• Intelligent Data Analysis (20 credits)
• Machine Learning (20 credits)
• Medical Imaging (10 credits)
• Neural Computation (20 credits)
• Observational Cosmology (10 credits)
• Physical Principles of Radar (10 credits)
• The Life and Death of Stars (10 credits)
• Semester 2:
• Atomic Physics (10 credits)
• Chaos and Dynamical Systems (10 credits)
• Condensed Matter Physics (10 credits)
• Evolution of Cosmic Structure (10 credits)
• Exoplanets (10 credits)
• Images and Communications (10 credits)
• Natural Language Processing (20 credits)
• Nuclear Physics (10 credits)
• Particle Physics (10 credits)
• Physics Critique (10 credits)
• Physics Teaching in Schools (10 credits)
• Radiation and Relativity (10 credits)

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Year 4:

• Core Module:
• Research Project:
• Project Dissertation (20 credits)
• Project Planning and Preliminary Report (10 credits)
• Project Seminar and Viva (20 credits)
• Optional Modules:
• Select 70 credits (40 credits in semester 1 and 30 credits in semester 2) from a selection including:
• Semester 1:
• Advanced Particle Physics Techniques (10 credits)
• Algorithms for Data Science (20 credits)
• Complex Variable Theory (10 credits)
• Current Topics in Particle Physics (10 credits)
• Fission and Fusion (10 credits)
• Inference from Scientific Data (10 credits)
• Intelligent Data Analysis (20 credits)
• Machine Learning (20 credits)
• Mathematical Foundations of Artificial Intelligence (AI) and Machine Learning (ML) (20 credits)
• Nanophotonics (10 credits)
• Neural Computation (Extended) (20 credits)
• Observational Cosmology (10 credits)
• Phase Transitions (10 credits)
• Physics of Renewable Energy (10 credits)
• Quantum Mechanics 4 (10 credits)
• Storing and Managing Data (20 credits)
• Superconductivity (10 credits)
• The General Theory of Relativity (10 credits)
• Ultracold Atoms and Quantum Gases (10 credits)
• Semester 2:
• Advanced Condensed Matter Physics (10 credits)
• Condensed Matter Physics (10 credits)
• Current Topics in Data Science (20 credits)
• Dynamics and Modelling of Weather and Climate (20 credits)
• Evolution of Cosmic Structure (10 credits)
• Exoplanets (10 credits)
• Images and Communications (10 credits)
• Many Particle and Quantum Field Theory (10 credits)
• Nuclear Physics (10 credits)
• Physics of Renewable Energy (10 credits)
• Quantum Optics (10 credits)
• Relativistic Astrophysics (10 credits)
• Visualisation (20 credits)

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Assessment:

Modules are assessed through a variety of methods, including:

• Exams
• Class tests
• Problem sheets
• Lab assignments
• Project reports
There is a strong emphasis on project work in the final year of the degree course. Lab work is assessed continuously throughout the term.

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Teaching:

The program is taught by experts in physics and computer science. Most modules are delivered through traditional lectures given by active physics researchers. Students also learn through tutorials, examples classes, guided study, laboratory practicals, and project work. Lab work is an integral part of the degree courses, and computing and transferable skills are interwoven into the studies.

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Careers:

Graduates of the Physics with Data Science MSci program are highly employable and can pursue a wide range of careers in academia, industry, and finance.

• Example Employers:
• NHS - Medical Physics
• Rolls-Royce
• EDF Energy
• BAE Systems
• Barclays Capital
• PriceWaterhouse Coopers
• Accenture - Technology Services
• Example Careers:
• Scientific researcher
• Medical physicist
• Energy consultant
• Defence analyst
• Meteorologist
• Statistician
• Financial services analyst
• Business consultant

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Other:

• The program is accredited by the Institute of Physics.
• The University of Birmingham has a Careers Network that provides a wealth of opportunities to develop career skills and find internships.
• The program includes a year-long data science research project in Year 4.
• Students have the opportunity to study modules from the School of Computer Science on topics such as Machine Learning and Intelligent Data Analysis, and Neural Computation.
• The program is highly personal, with weekly tutorials in the first two years with an academic member of staff and no more than four students.
• Lecturers have an open door policy, and elected student representatives meet weekly with staff to resolve any issues quickly.
• The program offers flexibility, with BSc and MSci versions identical for the first two years.
• The University of Birmingham has world-class teaching facilities, including state-of-the-art study spaces, computing suites, and teaching laboratories.
• The University of Birmingham has research facilities, including a particle accelerator, the MC40 cyclotron, and laboratories used for the construction of detectors and electronics used in experiments at the LHC, CERN.
• The University of Birmingham is home to one of the four UK Quantum Technology hubs, which is developing state-of-the-art quantum sensors.