Mathematics and Physics MMath
AAA at A level, Physics and Mathematics; graduates earn a median £30,000 three years on.
Typical A level offer
AAA
Physics and Mathematics · 100% of entrants came with A levels · 85% stay on after year 1 · York course page, Discover Uni
Year 13 · applying
What do you need to get in?
AAAtypical A level offer; aaa including physics and mathematics.
Typical offer — the grades most applicants are asked for. Contextual offer: ABB, for applicants from under-represented backgrounds.
York course page, read 19 September 2026 · Discover Uni entry profile
- 1Physics and Mathematics
Who actually got in: 100% with A levels. 10% arrived with 208 or more UCAS tariff points — roughly A*A*A or better. Based on 15 entrants.
UCAS tariff points — a points scale for grades: A* = 56, A = 48, so A*A*A = 160. Entrants’ totals include extra subjects.
Other qualifications3
| Qualification | Typical offer | Required subjects |
|---|---|---|
| IB | 36 points36 points overall, including 6 in Higher Level Mathematics (either Analysis and Approaches or Applications and Interpretations) and 5 in Higher Level Physics | 6 in Higher Level Mathematics |
| Scottish Highers | AB | — |
| Advanced Highers | AB in Physics and Mathematics plus | — |
Years 1–4
What do you study?
6compulsory modules in year 1
Compulsory modules this year: mathematics & statistics 39% · natural sciences 37% · digital & ict skills 14% · transversal skills 7%.
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.
York course page · optional modules vary by year
Year 1 · 6 core · 120 credits ≈ 1,200 hours
- Foundations and Calculus
What you learn (8)
- prove elementary results concerning sets and their properties
- prove elementary results concerning functions and their properties
- apply differentiation techniques to solve calculus problems
- apply integration techniques to solve calculus problems
- perform calculations with vectors and complex numbers to solve problems
- prove rigorous statements about the behaviour of limits
- solve problems relating limits to derivatives and integrals
- use a computer algebra system to solve module-related mathematical problems
- Multivariable Calculus and Matrices
What you learn (9)
- solve second-order differential equations using standard techniques
- construct a Fourier series expansion of a function
- construct a Taylor series expansion of a function
- differentiate functions of several variables
- integrate functions of several variables
- perform algebraic operations on matrices
- apply matrix methods to solve systems of linear equations
- use computer algebra software to solve multivariable calculus problems
- use computer algebra software to solve matrix algebra problems
- Mathematical Programming and Skills
What you learn (12)
- write programs using variables, expressions and assignments
- construct loops and conditional structures in code
- build functions and arrays to perform mathematical operations
- create classes and objects for mathematical applications
- apply inheritance and dynamic methods in program design
- search scientific literature relevant to a mathematical topic
- synthesise findings from scientific sources into a coherent summary
- typeset mathematical documents using LaTeX
- collaborate with peers to produce a shared report
- compile a professional-standard integrated report
- reflect on personal development of programming and research skills
- articulate acquired skills for professional career applications
- Classical and Quantum Waves
What you learn (5)
- formulate wave phase and amplitude using complex-exponential and trigonometric forms
- construct mathematical models of interference, diffraction and resonance
- apply wave theory to real-world oscillators and optical systems
- explain how quantum waves differ from classical wave theory
- solve one-dimensional time-independent problems using the schrodinger equation
- Classical Mechanics and Laboratories
What you learn (11)
- explain how newtonian postulates enable mathematical formulation of mechanics problems
- apply force, torque, momentum and energy concepts to derive equations of linear motion
- solve linear motion problems using kinematic methods
- solve rotational motion problems using dynamic methods
- plan a physics experiment to test a given hypothesis
- execute and record experimental procedures accurately
- appraise and discuss experimental findings
- identify sources of experimental uncertainty
- evaluate experimental uncertainties using normal distribution properties
- apply techniques to reduce experimental uncertainty
- produce a scientific report following standard structure and conventions
- Electromagnetism and Relativity
What you learn (15)
- describe electromagnetic fields as vector quantities
- explain how forces act on charges within electric and magnetic fields
- relate scalar potential functions to electric fields and potential energy
- calculate electric fields produced by charge distributions
- calculate magnetic fields produced by current distributions
- calculate potential energies associated with charge and current distributions
- apply Maxwell's equations in integral form to solve physical problems
- apply Maxwell's equations in differential form to solve physical problems
- explain how Maxwell's equations predict electromagnetic waves
- describe the postulates of special relativity
- derive the Lorentz transformations from relativity postulates
- solve problems involving time dilation for objects in relative motion
- solve problems involving length contraction for objects in relative motion
- solve problems involving relativistic energy of moving objects
- solve problems involving relativistic momentum of moving objects
Year 2 · 6 core · 120 credits ≈ 1,200 hours
- Vector and Complex Calculus
What you learn (11)
- calculate gradient, divergence, curl and laplacian of scalar or vector fields
- perform dot and cross product operations on vectors
- apply algebraic and differential identities involving vector operators
- evaluate integrals of scalar fields over curves, surfaces and solids
- transform triple integrals using substitution or cylindrical and spherical coordinates
- apply the fundamental theorem of line integrals to evaluate vector field integrals
- apply Green's, Gauss' and Stokes' theorems to evaluate integrals
- apply the Cauchy-Riemann equations to test differentiability of complex functions
- determine whether a complex function is analytic
- compute the Laurent series expansion of a complex function
- apply the residue theorem to evaluate definite integrals
- Classical Dynamics
What you learn (11)
- perform vector operations relevant to mechanics problems
- formulate many-body dynamics problems using vector methods
- apply different reference frames to dynamics problems
- explain the relationship between conservation laws and equations of motion
- investigate orbital properties arising from gravitational motion
- apply Lagrangian formulation to mechanical systems
- apply Hamiltonian formulation to mechanical systems
- relate Lagrangian and Hamiltonian frameworks to broader physical theories
- classify equilibrium points in one-dimensional dynamical systems
- analyse bifurcations in one-dimensional dynamical systems
- construct and interpret phase portraits for two-dimensional systems
- Quantum and Continuum Dynamics
What you learn (6)
- solve the wave equation in one and two dimensions
- describe properties of harmonic travelling waves and wave packets
- describe different types of ideal fluid flow
- solve the Schroedinger equation for simple quantum systems
- compute the energy spectrum of the harmonic oscillator
- compute the energy spectrum of the hydrogen atom
- Quantum, Atomic, Nuclear and Particle Physics
What you learn (32)
- interpret the time-dependent schrodinger equation
- derive the time-independent schrodinger equation from the time-dependent form
- construct quantum operators for physical observables
- calculate eigenfunctions and eigenvalues for multidimensional quantum systems
- calculate expectation values for quantum systems
- determine how quantum states evolve over time in multidimensional systems
- apply quantum mechanics to particles in symmetric potentials
- discuss quantum numbers arising from potential symmetries
- relate quantum system behaviour to the postulates of quantum mechanics
- describe atomic physics models
- define degeneracy in quantum systems
- calculate degeneracy in atomic systems
- use spectroscopic notation to describe atomic states
- explain how spectroscopic measurements are obtained
- construct and compare atomic energy level diagrams
- apply selection rules to atomic transitions
- describe the standard model particles including fermions and bosons
- illustrate particle interactions using feynman diagram vertices
- derive baryon and meson properties from quark substructure
- discuss the origin of hadron substructure
- discuss the properties of leptons
- illustrate leptonic decay modes using feynman diagrams
- determine conservation laws in standard-model reactions from feynman diagrams
- relate hadron decay modes to their quark structure
- discuss the significance of standard model particles in atomic and nuclear systems
- apply the semi-empirical mass formula to explain the chart of nuclides
- discuss key physics concepts of nuclear reaction and decay processes
- apply nuclear physics concepts to calculate decay and reaction quantities
- determine energies involved in nuclear reactions and processes
- relate nuclear energy quantities to nuclear stability and drip lines
- apply shell model rules to predict nuclear quantum properties
- discuss nuclear force properties in terms of exchange particles
- Thermodynamics and Electromagnetism
What you learn (9)
- explain key principles of electromagnetism
- describe standard mathematical formulations used to express electromagnetic laws
- apply Maxwell's equations to analyse electromagnetic phenomena
- use mathematical and computational tools to solve unfamiliar electromagnetism problems
- solve problems relating to heat and work transfer
- calculate changes in entropy for thermodynamic systems
- calculate thermodynamic properties of solids, liquids and gases using equations of state
- apply simplifying assumptions to model material behaviour
- explain how materials undergo phase changes
- Statistical and Solid State Physics
What you learn (6)
- derive macroscopic material properties from particle-level statistical models
- describe classical and quantum statistical distributions
- solve physics problems using statistical distribution functions
- apply statistical methods to analyse real physical systems such as solids
- describe crystalline microscopic ordering using lattice terminology
- apply electron behaviour models to distinguish insulators, metals and semiconductors
Year 3 · 0 core, 20 optional
20 optional modules
- Advanced Sensors and Instrumentation
What you learn (11)
- analyse how sensors convert physical quantities into measurable signals
- describe the operating principles of various sensor types
- identify limitations of different sensor technologies
- explain how sensors contribute to control system design
- analyse how application requirements determine sensor selection
- design a basic control system for a sensing application
- explain advanced technical concepts clearly and precisely
- evaluate advanced technical concepts for accuracy
- apply appropriate mathematical techniques to solve complex problems
- apply problem-solving and critical analysis skills to engineering tasks
- apply mathematical skills to analyse engineering problems
- Cryptography
What you learn (8)
- identify weaknesses in classical cryptosystems
- exploit identified weaknesses to break classical ciphers
- apply public key cryptographic protocols to solve numerical problems
- exploit weaknesses of public key protocols in simple scenarios
- perform calculations involving the mathematical structure of AES
- apply quantum information postulates to solve calculations
- describe the sequence of steps in the BB84 protocol
- explain why the BB84 protocol is secure
- Quantum Theory and Quantum Information
What you learn (7)
- describe the axiomatic structure of finite-dimensional quantum theory
- explain the concept of a quantum state and its measurement
- describe the role of probability in quantum mechanics
- use bra-ket notation to represent quantum states
- compare the informational power of quantum and classical systems
- construct simple quantum circuits
- describe the concept of a universal quantum computer
- Mathematical Ecology, Epidemiology and Evolution
What you learn (8)
- formulate dynamic mathematical models of ecological processes
- formulate mathematical models of disease transmission
- formulate mathematical models of evolutionary processes
- incorporate spatial effects into ecological and epidemiological models
- analyse mathematical models to predict dynamical behaviour
- explain interactions between ecological and evolutionary dynamics
- describe effects of randomness on eco-evolutionary and epidemiological models
- interpret mathematical results as biologically meaningful conclusions
- Mathematical Modelling: Nonlinearity, Uncertainty, and Computational Methods
What you learn (9)
- analyse qualitative behaviour of low-dimensional ODE systems
- identify bifurcations and transitions such as Hopf bifurcations and tipping points
- use computational tools to simulate and visualise dynamical systems
- relate computational outputs to analytical findings
- apply computational methods to model high-dimensional nonlinear systems
- simulate stochastic and discrete models of reaction dynamics
- apply stochastic differential equations to real-world modelling problems
- explain complex model behaviour using insights from simpler analogues
- critically evaluate contemporary research studies related to module topics
- Fluids
What you learn (8)
- identify key characteristics of a given fluid flow
- derive governing equations for a fluid flow problem
- specify appropriate boundary conditions for fluid flow problems
- solve simple fluid flow equations using analytical methods
- distinguish between different fluid flow regimes
- explain theoretical principles underlying fluid flow dynamics
- perform exact calculations for standard fluid flow problems
- apply approximation methods to calculate fluid flow properties
- Numerical Analysis
What you learn (5)
- select a suitable numerical method for a given mathematical problem
- apply a numerical technique to approximate a solution
- analyse the error behaviour of a numerical method
- determine the stability region of a numerical method
- implement numerical methods using Python
- Quantum Mechanics
What you learn (6)
- apply operator formalism to represent quantum states and observables
- explain wave function descriptions of quantum mechanics in position representation
- explain wave function descriptions of quantum mechanics in momentum representation
- describe the quantum harmonic oscillator model
- describe angular momentum theory in quantum mechanics
- identify quantum phenomena that differ from classical mechanics
- Partial Differential Equations
What you learn (8)
- solve basic first-order partial differential equations
- classify a second-order partial differential equation by type
- apply analytical methods to solve the wave equation
- apply analytical methods to solve the heat equation
- apply analytical methods to solve laplace and poisson equations
- analyse the error behaviour of finite-difference schemes for pdes
- evaluate the stability of finite-difference schemes for pdes
- compute numerical solutions of simple pdes using matlab
- Communicating Mathematics in Education
What you learn (10)
- describe the main responsibilities of a class teacher in preparing and delivering lessons
- explain approaches used by teachers to manage pupil behaviour and engagement
- describe how teachers collaborate and interact with colleagues in a school setting
- design a lesson plan that meets specified teaching objectives
- create teaching materials suited to a defined educational purpose
- explain mathematical concepts clearly to an individual pupil
- present mathematical ideas and skills effectively to a group of pupils
- apply theoretical concepts of mathematics education to classroom practice
- evaluate personal classroom experience to identify areas for improvement
- incorporate feedback from pupils and teachers into future practice
- Riemann Surfaces & Algebraic Curves
What you learn (5)
- apply the implicit function theorem to build complex charts for a curve
- construct algebraic curve examples of riemann surfaces
- calculate the genus of a given riemann surface
- compute the integral of a differential form over a riemann surface
- describe meromorphic functions constrained by a given divisor
- Astrobiology
What you learn (14)
- explain the chemical conditions that enabled life to emerge on Earth
- describe the astrophysical conditions that enabled life to emerge on Earth
- describe the biological conditions that enabled life to emerge on Earth
- identify solar system environments with potential to support life
- explain key biological processes relevant to habitability assessment
- identify potential biosignatures produced by biological activity
- evaluate astrophysical techniques used to detect biosignatures
- relate current research debates to planetary and exoplanetary science
- discuss philosophical questions concerning extraterrestrial life
- synthesise information from multiple disciplines into a coherent discussion
- write coherently on astrobiology topics using supporting evidence
- construct coherent arguments on astrobiology questions using facts and theory
- distinguish between factual evidence, theory and speculation in arguments
- communicate scientific ideas clearly to a non-specialist audience
- Nuclear and Particle
What you learn (12)
- explain how shell model mechanisms generate ground and excited nuclear states
- predict angular momentum and parity of nuclear states from shell model
- interpret published nuclear level schemes using single-particle and collective models
- extract evidence of excitation types from nuclear spectroscopic data
- explain the quantum-mechanical basis of alpha, beta and gamma decay
- calculate decay rates for alpha, beta and gamma processes
- analyse the physics of nuclear fission and fusion processes
- describe the operation of nuclear power reactors based on fission and fusion
- describe the fundamental interactions between elementary particles
- explain how composite particles form from elementary particles
- apply symmetry principles and force types to constrain particle reaction dynamics
- evaluate detectors and techniques used in modern particle physics experiments
- Condensed Matter Physics: Electrons in Solids
What you learn (15)
- describe models used to explain electronic interactions in solids
- explain the physical principles underlying electron behaviour models
- derive mathematical expressions for free and nearly free electron models
- apply free electron approximations to describe electrons in solids
- evaluate electron behaviour in solids under electric and magnetic fields
- explain how electronic structure determines optical properties of solids
- distinguish types of magnetic behaviour in solids
- distinguish types of dielectric behaviour in solids
- explain the fundamental principles of superconductivity
- describe the characteristic features of superconducting materials
- explain how surface effects alter electronic properties of solids
- describe transport phenomena occurring in materials
- apply transport phenomena concepts to practical material applications
- describe experimental techniques for probing electronic structure in solids
- evaluate the benefits and limitations of electron probing techniques
- Advanced Theoretical Techniques and Modelling Matter
What you learn (10)
- describe physical principles behind computational simulation methods for materials
- assess benefits and limitations of different material simulation approaches
- operate materials simulation software to model physical properties of matter
- apply simulation techniques to investigate physical properties of diverse materials
- evaluate simulated physical properties across different materials
- analyse simulation output data to derive material physical properties
- apply integral transform methods to solve differential equations
- interpret physical processes described by transformed differential equations
- extend differential equation solutions to account for nonlinear behaviour
- transform physical quantities between different coordinate systems and reference frames
- Medical Physics
What you learn (5)
- explain interactions of radiation with matter and biological tissue
- describe detectors and methods for monitoring radiation dose
- explain mri and pet imaging and how they are realised in devices
- use computer simulations to investigate medical-physics problems
- present applications of physics techniques in a medical case
- Stars and Galaxies
What you learn (9)
- describe how matter and radiation are distributed throughout a galaxy
- apply physical principles to explain stellar evolutionary processes
- explain the different phases present in the interstellar medium
- describe stellar evolution stages leading to and from the main sequence
- calculate stellar evolutionary endpoints based on initial stellar mass
- explain how stellar evolution affects the surrounding interstellar medium
- evaluate how radiation affects atomic and molecular interstellar components
- discuss processes underlying galaxy formation and evolution
- appraise extreme galactic phenomena including active galactic nuclei
- Relativity and Cosmology
What you learn (8)
- construct space-time diagrams to represent relativistic events
- apply four-vector formalism to describe relativistic motion
- describe the outcomes of the four classical experimental tests of general relativity
- explain black hole physics using semi-quantitative reasoning
- calculate the evolution of different universe models using cosmological equations
- explain the inflationary Big Bang theory and its supporting evidence
- describe the principles of gravitational wave astronomy
- explain how gravitational wave observations inform relativity and cosmology research
- Quantum Science and Technologies
What you learn (8)
- explain the fundamental principles of quantum computation
- describe basic techniques of quantum error correction
- identify criteria for physical systems to function as quantum computers
- describe proposed physical implementations of quantum computers
- explain the fundamental principles of quantum communication
- describe modern protocols used in quantum communication
- compare theoretical security with its practical implementation
- describe methods used for quantum key distribution
- Plasma Physics and Fusion
What you learn (6)
- describe the defining physical characteristics of a plasma state
- identify different theoretical models used to describe plasma behaviour
- identify real-world applications that rely on plasma physics
- explain the scientific principles underlying plasma-based technologies
- apply mathematical techniques to analyse plasma physics problems
- solve novel quantitative problems relating to fusion physics
Year 4 · 1 core, 16 optional · 60 credits ≈ 600 hours
- MPhys Research Project and Skills or Extended Independent Project in Mathematics
What you learn (15)
- plan and design an extended research project
- carry out an extended research investigation
- report findings of an extended research project
- investigate a physics topic using systematic critical methods
- apply experimental, computational or theoretical techniques to a physics problem
- organise own work independently to meet project objectives
- collaborate with internal and external research partners
- retrieve original source references from academic databases
- evaluate the credibility of retrieved scientific sources
- maintain a systematic record of research work in a notebook
- research and compose background material for a project
- apply advanced research methods to conduct a scientific investigation
- evaluate project findings against existing literature
- compose a written report presenting project outcomes
- present project outcomes orally to an audience
16 optional modules
- General Relativity
What you learn (3)
- apply tensor calculus and index notation accurately
- solve problems on curved-manifold geometry and the einstein equation
- interpret mathematical results of general relativity physically
- Directed Learning in Mathematics
What you learn (4)
- apply key techniques from the studied topic to solve advanced problems
- analyse advanced mathematical literature to demonstrate deep topic understanding
- explain key mathematical concepts clearly to staff or peers
- manage independent study to complete term assessments
- Quantum Field Theory
What you learn (6)
- apply relativistic field theory formalism to physical problems
- apply canonical commutation relations in quantum field calculations
- apply canonical anticommutation relations in quantum field calculations
- solve the Klein-Gordon equation for scalar fields
- solve the Dirac equation for spinor fields
- analyse symmetries of relativistic quantum fields
- Mathematical Modelling: Nonlinearity, Uncertainty, and Computational Methods
What you learn (11)
- analyse dynamics of low-dimensional ODE systems analytically
- identify qualitative behaviours such as periodicity, excitability and tipping points
- visualise analytic results using computational techniques
- apply computational methods to support analytical findings
- apply computational techniques to high-dimensional ODE systems
- simulate stochastic and discrete models of reaction systems
- apply stochastic differential equations to model complex systems
- explain complex model behaviour using insights from simpler analogues
- critically evaluate contemporary research studies related to module topics
- construct mathematical models of real-world systems
- analyse constructed models using module-based methods
- Riemann Surfaces and Algebraic Curves
What you learn (3)
- apply the implicit function theorem to build complex charts on algebraic curves
- construct algebraic curves as examples of Riemann surfaces
- calculate the genus of a Riemann surface
- Fluids
What you learn (6)
- analyse characteristics of a particular fluid flow
- formulate governing equations and boundary conditions for a flow
- solve fluid-flow equations analytically in simple cases
- interpret different fluid flow regimes
- apply theories underlying fluid flow dynamics
- formulate equations for novel fluid-flow systems
- Partial Differential Equations
What you learn (9)
- solve basic first-order partial differential equations
- classify a second-order partial differential equation by type
- apply analytical methods to solve the wave equation
- apply analytical methods to solve the heat equation
- apply analytical methods to solve laplace and poisson equations
- analyse the error of finite-difference methods for pdes
- compute numerical solutions of simple pdes using matlab
- solve inhomogeneous forms of the wave equation
- solve inhomogeneous forms of the heat equation
- Mathematical Ecology, Epidemiology and Evolution
What you learn (6)
- incorporate spatial effects into ecological and epidemiological models
- analyse mathematical models to predict long-term dynamical behaviour
- describe the influence of random variation on eco-evolutionary and epidemiological models
- translate mathematical findings into biologically meaningful conclusions
- connect current research studies to module topics
- develop computer code to generate numerical solutions supporting analytic results
- Quantum Theory and Quantum Information
What you learn (6)
- state the axioms of quantum theory in finite dimensions
- calculate probabilities using bra-ket notation for quantum states
- explain why quantum information is more powerful than classical
- construct quantum circuits and convert between circuit and operator notation
- explain what a universal quantum computer is
- apply advanced quantum-information concepts such as quantum operations
- From Subatomic to Nuclear Astrophysics
What you learn (5)
- explain nuclear structure models such as rotation and shape coexistence
- apply experimental techniques to analyse nuclear excited states
- explain gross properties of hadrons and mesons
- analyse how elemental abundance reflects astrophysical nucleosynthesis
- critique experimental techniques for astrophysical reaction rates
- Biophysics
What you learn (11)
- apply physical laws to construct models of biological systems
- analyse biological system models quantitatively
- critique assumptions underlying biophysical models
- evaluate how assumptions affect the validity of model results
- explain the physical principles underlying experimental biophysical techniques
- interpret key results obtained from biophysical experiments
- assess the defining features of biological systems studied
- evaluate the biological significance of these systems
- describe key physical principles behind major biological processes
- critically analyse experimental biophysical data
- reflect on personal professional skills gained through data analysis
- Cosmic Horizons
What you learn (2)
- evaluate current astrophysical understanding using research and computational sources
- identify discrepancies and gaps between models and observational data
- Advanced Quantum Mechanics
What you learn (10)
- relate symmetries in quantum systems to associated conservation laws
- calculate time evolution of a quantum wavefunction
- assess effects of time evolution on measurable physical quantities
- derive first-order time-dependent perturbation theory results
- apply first-order perturbation theory to quantum systems
- calculate geometric phases in adiabatically evolving quantum systems
- explain quantum mechanical laws governing systems of multiple particles
- apply many-particle quantum mechanics to solve problems
- derive general results of quantum angular momentum theory
- apply angular momentum theory to quantum mechanical problems
- Scientific Supercomputing
What you learn (8)
- describe different categories of high-performance computing hardware
- select appropriate hardware for a given computational task
- develop parallel software programs to solve scientific problems
- use profiling tools to locate performance bottlenecks in code
- devise strategies to resolve identified performance bottlenecks
- explain the operation of high-performance computing systems
- operate a high-performance computing system
- analyse a scientific problem to select a suitable parallelisation strategy
- Advanced Condensed Matter Physics
What you learn (6)
- explain the significance of the nanoscale regime in materials behaviour
- describe fabrication methods used to produce nanomaterials and nanodevices
- describe characterisation techniques applied to nanomaterials and nanodevices
- determine atomic structure from electron microscopy data
- describe applications and devices based on nanomaterials and nanostructures
- explain the operating principles and key parameters of nanodevices
“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?
£30,000median pay three years after graduating
Lower quarter£24k
Median£30k
Upper quarter£40k
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 125 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 13, 24, 23
Half of graduates earned between £24,000 and £39,500. Five years on, the median is £37,500. 85% were in work or further study 15 months after finishing; 90% of those in work were in professional or managerial jobs.
All outcome figures7
| Measure | Value | Based on |
|---|---|---|
| Continue after year 115% left | 85% | 15 |
| In work or study, 15 months on25% studying | 85% | 55 |
| Professional or managerial job | 90% | 25 |
| Pay 15 months on, median | £34,000 | 20 |
| Pay 3 years on, median | £30,000 | 125 |
| Pay 5 years on, median | £37,500 | 145 |
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.
York 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. International students: £33,500 a year (2027/28).
National Student Survey 2024-26
What do students say?
90%agreed the course was good overall (question 26)
NSS — a yearly survey of final-year students at every UK university; 67% of this course’s final year answered. Small groups can swing a lot year to year.
National Student Survey, via Discover Uni · 10 students answered
Highest: 100% agreed on question 1; lowest: 60% on question 24.
All questions26
| Question | Agree |
|---|---|
| Question 1 | 100% |
| Question 2 | 100% |
| Question 3 | 90% |
| Question 4 | 90% |
| Question 5 | 90% |
| Question 6 | 80% |
| Question 7 | 90% |
| Question 8 | 80% |
| Question 9 | 90% |
| Question 10 | 90% |
| Question 11 | 90% |
| Question 12 | 90% |
| Question 13 | 100% |
| Question 14 | 70% |
| Question 15 | 100% |
| Question 16 | 100% |
| Question 17 | 70% |
| Question 18 | 80% |
| Question 19 | 90% |
| Question 20 | 100% |
| Question 21 | 100% |
| Question 22 | 100% |
| Question 23 | 90% |
| Question 24 | 60% |
| Question 25 | 70% |
| Question 26 | 90% |
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 York’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 York is a trade mark of the university; sch.today is independent of it.