Mathematics and Physics MMath&Phys
A*AA at A level, A* in Mathematics, A in Further Mathematics and A in Physics; graduates earn a median £33,500 three years on.
Typical A level offer
A*AA
A* in Mathematics, A in Further Mathematics and A in Physics · 95% of entrants came with A levels · 95% stay on after year 1 · Warwick course page, Discover Uni
Year 13 · applying
What do you need to get in?
A*AAtypical A level offer; a*aa to include a* in mathematics, a in further mathematics and a in physics. for students not taking a level further mathematics, the typical offer is a* (mathematics), a* (physics) and a in a third
Typical offer — the grades most applicants are asked for. Contextual offer: A*AB, for applicants from under-represented backgrounds.
Warwick course page, read 19 September 2026 · Discover Uni entry profile
- 1A* in Mathematics, A in Further Mathematics and A in Physics
Who actually got in: 95% with A levels, 5% with the IB. 50% arrived with 208 or more UCAS tariff points — roughly A*A*A or better. Based on 45 entrants.
UCAS tariff points — a points scale for grades: A* = 56, A = 48, so A*A*A = 160. Entrants’ totals include extra subjects.
Other qualifications4
| Qualification | Typical offer | Required subjects |
|---|---|---|
| IB | 38 points38 to include 7 in Higher Level Mathematics ('Analysis and Approaches' only) and 6 in Higher Level Physics | 7 in Higher Level Mathematics |
| BTEC | —We will consider applications from students taking a BTEC in a relevant Science/Engineering alongside A level Maths and Further Maths on an individual basis. | — |
| Advanced Highers | AA in Advanced Higher Mathematics and Advanced Higher Physics and AAA in HighersAA in Advanced Higher Mathematics and Advanced Higher Physics and AAA in Highers in 3 further subjects. | — |
| Access | 45 Credits at Level 3, including Distinction in 33 Level 3 credits and Merit in We will consider applicants returning to study who are presenting a QAA-recognised Access to Higher Education Diploma on a case-by-case basis. Typically, we require 45 Credits at Level 3, including Di | — |
Years 1–4
What do you study?
11compulsory modules in year 1
Compulsory modules this year: mathematics & statistics 63% · natural sciences 30% · digital & ict skills 4% · engineering & manufacturing 3%.
Module — one course unit, usually a term or a year long; “core” means everyone takes it. One UK credit is about ten hours of study; a full year is 120 credits.
Warwick course page · optional modules vary by year
Year 1 · 11 core · 120 credits ≈ 1,200 hours
- Sets and Numbers
What you learn (4)
- apply properties of standard number systems
- use set notation and quantifiers accurately
- describe functions and relations using formal notation
- apply different proof techniques to mathematical statements
- Mathematical Analysis 1
What you learn (7)
- describe the structure and properties of the real number system
- explain the concept of infinity and its use in mathematical analysis
- identify limits of sequences and series
- distinguish between conditional and absolute convergence of series
- apply convergence tests to determine series behaviour
- describe the properties of continuous functions
- explain the characteristics of absolutely continuous functions
- Methods of Mathematical Modelling 2
What you learn (13)
- evaluate scalar-valued functions of several variables
- evaluate vector-valued functions of several variables
- describe parametric representations of curves
- describe parametric representations of surfaces
- apply coordinate transformations to mathematical expressions
- explain the relationships linking line, surface and volume integrals
- evaluate line, surface and volume integrals using integral theorems
- compute partial derivatives and gradients of multivariable functions
- compute the Jacobian and directional derivative of a function
- compute the divergence and curl of a vector field
- interpret the geometric meaning of a multivariable Riemann integral
- integrate functions over simple regions
- justify changes to area and volume elements under coordinate conversion
- Methods of Mathematical Modelling 1
What you learn (12)
- describe the stages involved in constructing a mathematical model
- formulate a simple mathematical model for a given situation
- analyse the behaviour of a simple mathematical model
- apply scaling and non-dimensionalisation to simplify a model
- apply linear stability analysis to identify dominant dynamics
- explain which factors drive the behaviour of a dynamical system
- solve first order ordinary differential equations
- solve second order ordinary differential equations
- interpret the qualitative behaviour of solutions to differential equations
- solve simple difference equations
- relate difference equations to their continuous differential equation counterparts
- describe basic techniques for numerically approximating solutions
- Linear Algebra
What you learn (13)
- define vector spaces and their properties
- determine whether a set of vectors is linearly independent
- identify a basis and calculate the dimension of a vector space
- explain the concept of a linear transformation
- apply linear transformations to vectors and spaces
- perform matrix manipulations using row and column operations
- apply matrix reduction techniques to solve systems of linear equations
- calculate determinants of n by n matrices
- compute cofactors and adjoint matrices
- explain how determinants and adjoints relate to solving linear systems
- compute eigenvalues and eigenvectors of a matrix
- interpret the geometric meaning of eigenvalues and eigenvectors
- describe linear transformations between euclidean spaces
- Mathematical Analysis 2
What you learn (10)
- determine whether a function is differentiable at a point
- compute higher-order derivatives of a function
- explain key properties of differentiable functions
- construct the Taylor series of a given function
- apply Taylor's theorem to estimate approximation error
- determine when a function can be represented by a power series
- construct the Riemann integral from first principles
- explain the theoretical basis of the Riemann integral's construction
- explain conditions guaranteeing integrability of continuous functions
- apply the Fundamental Theorem of Calculus to evaluate integrals
- Physics Foundations
What you learn (10)
- apply dimensional analysis to relate physical quantities
- describe characteristics of solid, liquid and gas phases
- apply kinetic theory to explain gas behaviour
- solve problems involving heat transfer and work using thermodynamic laws
- solve problems on travelling and standing waves
- solve problems involving the doppler effect
- apply boundary conditions to determine normal modes
- describe the electromagnetic nature of light
- explain polarization of light
- explain the role of refractive index in light behaviour
- Classical Mechanics & Special Relativity
What you learn (6)
- apply Newton's second law to solve motion problems
- calculate kinetic and potential energy in mechanical systems
- identify equations describing forced and damped oscillations
- solve differential equations of forced and damped oscillators
- explain how coordinates transform between inertial reference frames
- apply the lorentz transformation to solve relativity problems
- Quantum Phenomena
What you learn (12)
- explain experimental evidence supporting wave-particle duality of light
- explain experimental evidence supporting wave-particle duality of matter
- describe the historical development of Schrödinger's equation
- discuss interpretive issues arising from solutions of Schrödinger's equation
- apply the time-independent Schrödinger equation to simple one-dimensional potentials
- classify elementary particles according to their properties
- assign correct quantum numbers to quark and lepton flavours
- explain the link between physical symmetries and conservation laws
- describe methods used to study elementary particles experimentally
- characterise sources of natural radioactivity
- characterise cosmic ray phenomena
- characterise solar and atmospheric neutrino phenomena
- Electricity and Magnetism
What you learn (14)
- state Gauss's law for electric and magnetic fields
- state Ampere's law for magnetic fields
- calculate electric fields for simple charge distributions using Gauss's law
- calculate the force on a charged particle in an electric field
- calculate the force on a charged particle in a magnetic field
- analyse the motion of charged particles under combined electric and magnetic fields
- state Faraday's law of electromagnetic induction
- describe inductance using Faraday's law
- describe motional electromotive force using Faraday's law
- apply Kirchhoff's laws to analyse circuit currents and voltages
- apply Maxwell loop analysis to determine circuit currents
- use complex impedance to determine current-voltage characteristics of AC circuits
- explain how electric fields interact with materials
- explain how magnetic fields interact with materials
- Physics Programming Workshop
What you learn (7)
- write python programs to solve given tasks
- formulate simple maths and physics problems in computational terms
- solve differential equation, linear algebra and integration problems using python
- apply scientific and graphical libraries to analyse data
- perform statistical calculations using python
- apply good software design principles to code
- present scientific results in graphical form
Year 2 · 6 core · 75 credits ≈ 750 hours
- Mathematical Analysis 3
What you learn (7)
- compute contour integrals using cauchy's integral formulas
- apply cauchy's integral formulas to solve related problems
- distinguish uniform convergence from pointwise convergence of functions
- describe properties of the limit function of a convergent sequence
- apply the cauchy-riemann equations to test complex differentiability
- manipulate complex power series to represent analytic functions
- represent derivatives of multivariable functions as linear maps
- Quantum Mechanics and its Applications
What you learn (10)
- explain the origin of quantum numbers n, l, m and s
- relate quantum numbers to the structure of the periodic table
- explain the role of hermitian operators in quantum mechanics
- interpret eigenvalue equations in a quantum mechanical context
- explain the correspondence principle linking classical and quantum physics
- derive the electronic states of a hydrogen atom using quantum mechanics
- describe the free-electron model of metallic behaviour
- explain the concept of energy bands in solids
- apply band theory to explain properties of metals and semiconductors
- apply quantum theory to explain behaviour of elementary particles and nuclei
- Statistical Mechanics, Electromagnetic Theory and Optics
What you learn (14)
- explain the ergodic hypothesis in statistical mechanics
- define thermal equilibrium across different statistical ensembles
- define the partition function of a statistical system
- calculate thermodynamic averages using the partition function
- apply Fermi-Dirac and Bose-Einstein distributions to quantum systems
- describe the conceptual structure of statistical mechanics
- explain the relationship between statistical mechanics and classical thermodynamics
- express Maxwell's equations in integral and differential forms
- manipulate Maxwell's equations to solve electromagnetic problems
- derive boundary conditions at interfaces between linear isotropic materials
- derive plane-wave solutions of Maxwell's equations in dielectric media
- derive plane-wave solutions of Maxwell's equations in ohmic conductors
- describe how light interacts with optical materials
- explain fundamental principles of geometrical optics
- Hamiltonian and Fluid Mechanics
What you learn (13)
- derive the Euler-Lagrange equations from a given Lagrangian
- solve the Euler-Lagrange equations for simple mechanical systems
- construct the Hamiltonian function for a given mechanical system
- derive Hamilton's equations from the Hamiltonian function
- explain how constraints affect the choice of generalised coordinates
- relate conserved quantities to symmetries in generalised coordinates
- apply dimensional analysis to characterise fluid flow behaviour
- explain the significance of the Reynolds number in flow regimes
- describe the concept of the boundary layer in fluid flow
- describe the Navier-Stokes equations governing incompressible fluid motion
- identify appropriate boundary conditions for incompressible fluid flow
- simplify the equations of motion for incompressible irrotational flow
- solve simplified flow equations for basic cases such as vortices
- Methods of Mathematical Physics
What you learn (8)
- express a function as a Fourier series
- convert a function into its Fourier transform
- explain the physical basis of diffraction and interference phenomena
- apply Lagrange multipliers to optimise a constrained function
- convert vector representations between different coordinate systems
- identify physical examples of tensors
- derive Stokes's theorem
- apply Stokes's theorem to solve physical problems
Year 3 · 5 core · 60 credits ≈ 600 hours
- Fluid Dynamics
What you learn (3)
- explain how the governing equations of fluid motion are derived
- apply mathematical methods to find approximate solutions to fluid flow equations
- interpret mathematical solutions in terms of practical fluid flow problems
- Quantum Physics of Atoms
What you learn (8)
- apply time-independent perturbation theory to quantum systems
- apply time-dependent perturbation theory to quantum systems
- apply variational methods to estimate quantum energy states
- explain the concept of electron spin in atomic structure
- explain how the pauli exclusion principle governs electron configuration
- explain the origin of atomic spectral lines
- explain how electron configuration determines the structure of the periodic table
- describe the phenomenon of resonance in two-level quantum systems
- Electrodynamics
What you learn (8)
- apply the vector potential to electromagnetic problems
- express Maxwell's equations in Lorentz invariant form
- rewrite Maxwell's equations using four-vector notation
- solve electrodynamics problems using four-vector methods
- describe the physical mechanisms of electromagnetic radiation and scattering
- describe propagation of electromagnetic waves in free space
- describe propagation of electromagnetic waves in waveguides
- calculate electromagnetic fields from given source distributions using Maxwell's equations
- Laboratory for Mathematics & Physics Students
What you learn (9)
- conduct a collaborative experimental investigation with peers
- write a research-style report presenting experimental findings
- construct computational models to represent complex physical systems
- use simulation tools to analyse system behaviour
- deliver an oral presentation of findings to peers
- calculate random and systematic measurement uncertainties
- evaluate the impact of uncertainty sources on experimental results
- discuss health and safety considerations in experimental planning
- evaluate practical issues affecting the design and analysis of an experiment
- Kinetic Theory
What you learn (5)
- derive the Boltzmann equation from kinetic theory principles
- solve the Boltzmann equation for given physical conditions
- formulate boundary value problems for phase space distributions
- solve boundary value problems describing time evolution of distributions
- apply kinetic theory to analyse model physical systems
Year 4 · 1 core, 8 optional · 45 credits ≈ 450 hours
- Physics Project
What you learn (5)
- conduct an independent research investigation in physics
- analyse data collected during a physics investigation
- write a structured scientific report describing research work
- present research findings on a poster to an audience
- defend research findings and methodology in response to questions
8 optional modules
- Dynamical Systems
What you learn (3)
- identify minimality, transitivity, mixing and conjugacy in dynamical systems
- describe examples of dynamical systems and their hyperbolicity properties
- construct symbolic dynamical models for given dynamical systems
- Fourier Analysis
What you learn (2)
- derive fundamental properties of Fourier series and transforms
- apply convolution results with good kernels to solve partial differential equations
- Population Dynamics: Ecology & Epidemiology
What you learn (3)
- describe classical ecological and epidemiological models and their parameters
- apply classical models to address real-world ecological and epidemiological questions
- perform phase-plane analysis to assess steady states and their stability
- Continuum Mechanics
What you learn (6)
- apply tensor algebra and calculus operations to solve problems
- describe mass, force and stress concepts within continuum models
- describe deformation, displacement and strain concepts within continuum models
- derive partial differential balance equations from conservation principles
- solve simplified continuum mechanics equations analytically
- interpret solutions to predict physical behaviour of continua
- Advanced Topics in Fluids
What you learn (4)
- simplify governing partial differential equations for fluid flow
- apply governing equations to specific fluid flow problems
- solve derived fluid flow equations using mathematical methods
- interpret mathematical solutions in terms of physical flow behaviour
- Mathematics of Neuronal Networks
What you learn (7)
- construct mathematical models of physiological structures like synapses and neurons
- test validity of mathematical models against physiological behaviour
- describe fundamental properties of stochastic differential equations
- derive probabilistic descriptions of dynamical system behaviour
- explain how network-level behaviour emerges from coupled component properties
- design artificial neural networks capable of pattern recall
- design artificial neural networks capable of pattern classification
- High Performance Computing and Machine Learning
What you learn (9)
- identify inefficiencies in serial scientific code
- correct inefficient sections of scientific code
- develop a parallel program using shared-memory techniques for physics problems
- develop a parallel program using message-passing techniques for physics problems
- build a basic GPU-accelerated program
- select a suitable programming paradigm for a computational task
- diagnose performance bottlenecks in parallel programs
- diagnose parallelisation errors in parallel programs
- design machine learning models for complex scientific data
“What you learn” restates each module’s published learning outcomes in our own words, as short skill statements in the same form as the GCSE and A level curriculum, with the help of an AI model; fields of knowledge follow the twelve fields of the knowledge sphere. The university’s module page, linked from each title, is the authoritative description.
After graduating
Where does it lead?
£33,500median pay three years after graduating
Lower quarter£28k
Median£34k
Upper quarter£44k
Median — the middle earner: half earned more, half less. Pay is for graduates of this subject at this university who finished in 2016-18, not adjusted for inflation; based on 120 graduates.
Discover Uni dataset (HESA and Office for Students, CC BY 4.0, contains HESA data); earnings from the Longitudinal Education Outcomes data (Department for Education) · aggregation level 24, 14, 13, 23
Half of graduates earned between £27,500 and £44,000. Five years on, the median is £42,000. 85% were in work or further study 15 months after finishing; 75% of those in work were in professional or managerial jobs.
All outcome figures7
| Measure | Value | Based on |
|---|---|---|
| Continue after year 15% left | 95% | 40 |
| In work or study, 15 months on40% studying | 85% | 15 |
| Professional or managerial job | 75% | 15 |
| Pay 15 months on, median | £34,000 | 30 |
| Pay 3 years on, median | £33,500 | 120 |
| Pay 5 years on, median | £42,000 | 150 |
Money
What does it cost?
£10,050a year for UK students, 2027/28 entry
Tuition fee loan — paid straight to the university; repayments start the April after you leave, at 9% of income above the threshold. UK fees are capped by government and rise with inflation; placement and study-abroad years are usually charged at a lower rate.
Warwick fees page · source
About £40,200 in fees over 4 years, covered by a tuition fee loan you repay only when earning above the threshold.
National Student Survey 2025-26
What do students say?
82%agreed the course was good overall (question 26)
NSS — a yearly survey of final-year students at every UK university; 92% of this course’s final year answered. Small groups can swing a lot year to year.
National Student Survey, via Discover Uni · 45 students answered
Highest: 98% agreed on question 3; lowest: 49% on question 24.
All questions26
| Question | Agree |
|---|---|
| Question 1 | 96% |
| Question 2 | 78% |
| Question 3 | 98% |
| Question 4 | 93% |
| Question 5 | 85% |
| Question 6 | 89% |
| Question 7 | 74% |
| Question 8 | 80% |
| Question 9 | 74% |
| Question 10 | 76% |
| Question 11 | 91% |
| Question 12 | 78% |
| Question 13 | 80% |
| Question 14 | 69% |
| Question 15 | 93% |
| Question 16 | 87% |
| Question 17 | 85% |
| Question 18 | 83% |
| Question 19 | 89% |
| Question 20 | 91% |
| Question 21 | 91% |
| Question 22 | 91% |
| Question 23 | 77% |
| Question 24 | 49% |
| Question 25 | 58% |
| Question 26 | 82% |
Question texts are published by the Office for Students; the dataset carries only the question numbers.
Modules, entry requirements and fees are facts read from University of Warwick’s course page on 2026-09-19 and may change; the university’s page is authoritative. Descriptions are not reproduced. Outcome figures are from the Discover Uni dataset. University of Warwick is a trade mark of the university; sch.today is independent of it.