BSc Physics and Astrophysics
Entry requirements
A Level: A*AA /AAAA to include A-level Mathematics and A-level Physics grades A*A (or AA as part of the four A level offer).. IB: 7,6,6 at HL, to include Mathematics and Physics, with a minimum of 32 points overall. 7 must be in Mathematics or Physics.. BTEC: options considered when combined with other Maths and Physics qualifications.
About this course
Bachelor of Science in Physics and Astrophysics, a physics and physics with astrophysics degree focused on the study of the universe and fundamental physical principles. Core topics include Statistics and Artificial Intelligence & Machine Learning. Students complete a final-year project alongside laboratory and observational training. The first year covers core foundations through Mathematics for Physicists 1, Classical Mechanics and Relativity, and Quantum Mechanics, Optics, Waves, and Electromagnetism. The second year progresses with Mathematics for Physicists 2, Statistical Physics and Optics, and Modern Physics. Optional and compulsory modules in the final year include Stars and Exoplanets, Gravitation, Cosmology and Galaxies, and Particle Physics, culminating in the Year 3 Physics Project.
Modules
- Statistics, Thermodynamics, and Electronics
- Quantum Mechanics, Optics, Waves, and Electromagnetism
- Classical Mechanics and Relativity
- Physics Laboratory 1
- Mathematics for Physicists 1
- Discover: Skills, Computing and Astrophysics
- Mathematics for Physicists 2
- Statistical Physics and Optics
- Quantum Mechanics and Electromagnetism 2
- Astrophysics Laboratory
- Challenge: Skills, Computing and Observational Astronomy
- Modern Physics
- Quantum Mechanics and Statistical Physics
- Year 3 Physics Project
- Observatory Laboratory
- Stars and Exoplanets
- Gravitation, Cosmology and Galaxies
- Particle Physics
- Nuclear Physics and Nuclear Power
- Advanced Dynamics, and Relativistic Fields
- Chaos Dynamical Systems and Complex Variables
- Medical Physics
- Atomic, Condensed Matter and Photonic Physics
- Professional Science Communication and Teaching
- Machine Learning and Inference from Data