Physics (with a year abroad) MPhys

University of York · honours · 5 years · optional placement year · year abroad · UCAS 8485course page ↗

AAA at A level, Physics and Mathematics; graduates earn a median £30,000 three years on.

Typical A level offer
AAA

Physics and Mathematics · 97% of entrants came with A levels · 89% 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

  1. 1Physics and Mathematics
Who actually got in: 97% with A levels, 1% with other higher education. 3% arrived with 208 or more UCAS tariff points — roughly A*A*A or better. Based on 145 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
QualificationTypical offerRequired subjects
IB36 points36 points overall, including 5 in Higher Level Mathematics (either Analysis and Approaches or Applications and Interpretations) or 6 in Standard Level Mathematics (Analysis and Approaches), plus 5 in 5 in Higher Level Mathematics
Scottish HighersAB—
Advanced HighersAB in Physics and Mathematics plus—
Years 1–5

What do you study?

5compulsory modules in year 1, 2 optional

Compulsory modules this year: natural sciences 46% · mathematics & statistics 32% · digital & ict skills 8% · transversal skills 8%.

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 · 5 core, 2 optional · 100 credits ≈ 1,000 hours
  • 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
    PHY00028C 20 cr
  • 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
    PHY00029C 20 cr
  • 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
    PHY00030C 20 cr
  • Mathematical, Computational and Professional Skills 1
    What you learn (23)
    • distinguish scalar quantities from vector quantities
    • apply vector methods to analyse physical systems
    • explain why complex numbers are useful in physics
    • apply complex numbers to find roots of polynomials
    • explain the concepts of differentiation and integration in one dimension
    • compute derivatives and integrals using standard techniques
    • explain the meaning of a partial derivative
    • calculate partial derivatives in multivariable series expansions
    • explain the significance of first and second order differential equations
    • solve differential equations to analyse physical systems
    • construct a basic python script
    • apply a python script to solve a physics problem
    • explain how physics skills prepare students for future employment
    • communicate ideas about career preparation effectively
    • reflect on personal skills to plan professional development as a physicist
    • describe the concept of scientific enterprise and roles available to physicists
    • engage in personal development activities relevant to physics careers
    • apply basic probability concepts to physical problems
    • apply binomial, poisson and normal distributions to data
    • calculate errors and standard error in measurements
    • identify ethical issues relevant to scientific practice
    • use computer software for numerical analysis in physics
    • use computer software to create graphs in physics
    PHY00031C 20 cr
  • Mathematical, Computational and Professional Skills 2
    What you learn (13)
    • compute multiple integrals in cartesian, spherical and cylindrical coordinates
    • apply multiple integration to solve a physical problem
    • define the fourier series of a periodic function
    • derive the fourier transform from a fourier series
    • describe directional rates of change of scalar and vector fields
    • apply python programming to model physical systems
    • apply python programming to analyse data
    • use office software to produce scientific presentations
    • communicate physics concepts in written form
    • communicate physics concepts orally
    • reflect on personal development through communication
    • work independently to complete tasks
    • collaborate effectively within a team
    PHY00033C 20 cr
2 optional modules
  • Mapping the Universe and Laboratories
    What you learn (12)
    • explain how the cosmic distance ladder determines scale and structure of the universe
    • describe methods used to observe planets, stars and galaxies
    • determine physical properties of astronomical objects from observational data
    • compare the design and location of different types of telescopes
    • acquire and analyse data collected from a telescope
    • evaluate evidence for dark matter and dark energy
    • outline the origin and fate of the universe according to the big bang model
    • identify the physical principles underlying key astrophysical phenomena
    • perform laboratory experiments demonstrating astrophysical principles
    • apply accurate record-keeping practices during experiments
    • assess and analyse experimental errors
    • write a scientific report following standard structure and style
    PHY00027C 20 cr
  • Theoretical Skills and Laboratories
    What you learn (12)
    • explain the rationale underlying mathematical modelling
    • apply dimensional analysis to suggest a model structure
    • derive model parameter values from experimental data
    • optimise parameter values within a mathematical model
    • write code in a scientific programming language
    • plan a scientific experiment to address a given problem
    • carry out an experiment and record data accurately
    • appraise and discuss experimental results
    • identify sources of experimental uncertainty
    • analyse experimental uncertainties to assess their impact
    • reduce experimental uncertainties through improved methods
    • write a scientific report following standard conventions
    PHY00032C 20 cr
Year 2 · 5 core, 2 optional · 100 credits ≈ 1,000 hours
  • 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
    PHY00032I 20 cr
  • Advanced Mechanics, Physics Laboratories and Skills
    What you learn (16)
    • derive lagrange's equations from hamilton's principle
    • apply lagrange's equations to model physical systems
    • explain derivation of conservation laws in lagrangian mechanics
    • apply the hamiltonian to show conservation of energy
    • plan an extended experimental investigation independently
    • execute experiments using appropriate techniques and data analysis
    • identify sources of experimental error
    • evaluate experimental results critically at an advanced level
    • present experimental findings to a professional standard
    • describe the stages of a recruitment process
    • prepare for and conduct an effective job interview
    • synthesise information from different disciplines into coherent responses
    • construct reasoned arguments supported by evidence and theory
    • adapt communication style to suit audience and purpose
    • create a plan to achieve personal career goals
    • develop python algorithms to model physical problems
    PHY00048I 20 cr
  • Mathematics, Professional Skills and Laboratories
    What you learn (17)
    • apply matrix methods to solve simultaneous equations
    • calculate eigenvectors and eigenvalues of a matrix
    • evaluate personal professional attributes valued by employers
    • communicate information and ideas to support employability
    • design a plan to achieve career objectives
    • identify ways to involve others in achieving professional goals
    • evaluate personal strengths and competencies relevant to a career sector
    • produce a CV and cover letter tailored to a target sector
    • use databases to find and evaluate relevant information
    • respond appropriately to peer expectations in group settings
    • use python libraries to implement computational algorithms
    • develop python code to solve physics problems
    • plan and conduct extended laboratory experiments
    • process and analyse experimental data using appropriate methods
    • assess sources of experimental error
    • critically discuss experimental results
    • present experimental findings clearly to an audience
    PHY00049I 20 cr
  • 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
    PHY00053I 20 cr
  • 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
    PHY00054I 20 cr
2 optional modules
  • Astrophysical Technologies and Space Science
    What you learn (8)
    • compare emission mechanisms producing high-energy radiation and neutrinos
    • assess how emission processes influence the observed flux at detectors
    • relate detector operation differences to underlying physical principles
    • calculate attenuation of high-energy radiation passing through shielding material
    • calculate the probability of radiation interacting with a target
    • explain how space weather events influence satellite design choices
    • apply orbital mechanics to calculate rocket trajectories
    • apply orbital mechanics to determine satellite paths
    PHY00046I 20 cr
  • Mathematical Techniques and Machine Learning
    What you learn (11)
    • classify numerical solutions obtained from differential equation solvers
    • determine whether a complex function is analytic
    • evaluate complex integrals using complex analysis techniques
    • identify extrema of a multivariable function under constraints
    • use special functions to construct a complete orthogonal set
    • select an appropriate machine learning algorithm for a given problem
    • implement a chosen machine learning algorithm
    • evaluate the suitability of a machine learning algorithm for a task
    • train a machine learning model on a dataset
    • evaluate the performance of a trained machine learning model
    • use a machine learning software library to analyse real datasets
    PHY00059I 20 cr
Year 3 · 1 core, 12 optional · 20 credits ≈ 200 hours
  • Advanced Experimental Laboratory
    What you learn (12)
    • research a departmental physics topic using literature and databases
    • attain understanding of current physics research comparable to final-year level
    • interpret scientific journal articles to identify key findings
    • extract relevant information from scientific publications
    • write concise scientific summaries of experimental work
    • compose an extended laboratory dissertation describing experimental work
    • evaluate the content and delivery of a PhD-level poster presentation
    • provide constructive feedback on a research poster
    • measure physical quantities using standard laboratory techniques
    • collect experimental data accurately in a laboratory setting
    • explain the physical principles underlying observed experimental results
    • maintain a professional and accurate laboratory notebook
    PHY00027H 20 cr
12 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
    ELE00075H 20 cr
  • Introduction to Clinical Engineering and Physiological Systems
    What you learn (5)
    • apply medical technologies for patient prevention, diagnosis and treatment
    • explain physiological concepts relevant to medical technology applications
    • describe the process of adopting new technology in healthcare organisations
    • solve problems using critical analysis in healthcare technology contexts
    • evaluate the efficacy of a proposed solution for real-world suitability
    ELE00085H 20 cr
  • 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
    PHY00061I 20 cr
  • 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
    PHY00071H 20 cr
  • Quantum Mechanics
    What you learn (16)
    • explain the link between commutators and measurement compatibility
    • calculate commutators of simple quantum operators
    • derive angular momentum operators in cartesian and spherical form
    • solve eigenvalue problems for angular momentum operators
    • explain how the central force theorem applies to spherically symmetric potentials
    • derive the analytical eigensolutions for the hydrogen atom
    • interpret the quantum numbers n, l and ml physically
    • solve the spin eigenproblem using pauli spin matrices
    • apply matrix formalism to analyse stern-gerlach experiments
    • derive first- and second-order energy corrections in perturbation theory
    • apply perturbation formulae to systems such as anharmonic oscillators
    • apply degenerate perturbation and variational methods to quantum problems
    • explain the procedure for quantising relativistic equations of motion
    • manipulate commutator and anticommutator expressions of operators
    • relate spin and gyromagnetic ratio to relativistic quantum mechanics
    • explain the origin of hydrogen fine structure using relativistic quantum theory
    PHY00072H 20 cr
  • 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
    PHY00073H 20 cr
  • 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
    PHY00074H 20 cr
  • 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
    PHY00075H 20 cr
  • 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
    PHY00076H 20 cr
  • 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
    PHY00077H 20 cr
  • 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
    PHY00078H 20 cr
  • 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
    PHY00079H 20 cr
Year 5 · 1 core, 13 optional · 60 credits ≈ 600 hours
  • MPhys Research Project and Skills
    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
    PHY00025M 60 cr
13 optional modules
  • Practical Skills in Virtual Anatomy and Morphology
    What you learn (7)
    • evaluate imaging modalities for suitability to a research question
    • describe advantages and disadvantages of virtual model creation approaches
    • create 3D virtual anatomical models using appropriate software methods
    • manipulate and visualise 3D anatomical models for analysis
    • use morphometric tools to quantify structural variation in models
    • apply statistical methods to analyse morphological variation
    • visualise statistical results of morphological analyses
    0990072 20 cr
  • Machine Vision and Human Machine Interaction
    What you learn (13)
    • evaluate core principles underlying machine vision systems
    • explain key concepts underpinning effective human-machine interaction
    • describe common machine vision algorithms
    • apply machine vision algorithms to simple perception tasks
    • apply human-machine interfaces to support human-machine collaboration
    • describe how machine vision supports human-machine interfacing
    • evaluate technical challenges in robot perception and interaction
    • evaluate ethical issues arising in human-robot interaction
    • design a machine vision system for a specific perception task
    • implement a machine vision system for human perception applications
    • design a basic human-machine interaction system
    • implement a basic human-machine interaction system
    • design systems capable of safely perceiving and interacting with their environment
    ELE00142M 20 cr
  • Product Design, Development and Commercialization
    What you learn (19)
    • apply idea generation techniques to produce new concepts
    • analyse generated ideas using structured analysis techniques
    • explain marketing tools used for branding new technologies
    • describe strategies for promoting new technology products
    • evaluate commercialisation options for an engineering business concept
    • produce a detailed business plan for a new engineering venture
    • conduct market research for a new business concept
    • test a new business concept using collected data
    • deliver a concise pitch to communicate a new business idea
    • analyse the resources needed to exploit a new market opportunity
    • estimate financial requirements for a new business venture
    • apply creative problem-solving techniques to business challenges
    • use effective decision-making techniques in business contexts
    • critically evaluate researched information for business decisions
    • write a concise business portfolio tailored to an audience
    • write a marketing plan appropriate to a target audience
    • deliver a workshop presentation on a business topic
    • present a summative elevator pitch to an audience
    • collaborate effectively within a team to achieve shared goals
    ELE00158M 20 cr
  • Future Healthcare and Computer Aided Diagnosis
    What you learn (11)
    • apply computer-aided design algorithms to diagnostic problems
    • describe basic human anatomy relevant to imaging
    • describe the principal bioimaging modalities used in medicine
    • evaluate biomedical images and their production characteristics
    • apply machine learning algorithms to process biomedical images
    • manage collection, storage and transfer of biomedical image data
    • interpret radiology images using systematic analysis methods
    • apply a standard computer-aided diagnosis algorithm to image analysis
    • assess physiological effects of radiation-tissue interaction
    • demonstrate good laboratory practice during experimental work
    • evaluate health and safety legislation affecting product development
    ELE00171M 20 cr
  • Medical Imaging and Physics
    What you learn (12)
    • apply engineering principles to explain body imaging and coordination systems
    • compare medical imaging modalities by their advantages and drawbacks
    • analyse the technical requirements of different imaging modalities
    • describe the anatomy and physiology relevant to bioimaging modalities
    • explain how radiation interacts with human tissue
    • evaluate biomedical imaging methods and their production processes
    • assess safety considerations and processing requirements of medical images
    • describe methods for acquiring medical images
    • describe methods for analysing medical images
    • identify different imaging modalities and their technical characteristics
    • describe machine learning algorithms used in image analysis
    • evaluate the safety risks of radiation-tissue interactions in imaging technologies
    ELE00173M 20 cr
  • 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
    PHY00032M 20 cr
  • 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
    PHY00033M 20 cr
  • Cosmic Horizons
    What you learn (2)
    • evaluate current astrophysical understanding using research and computational sources
    • identify discrepancies and gaps between models and observational data
    PHY00044M 20 cr
  • 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
    PHY00048M 20 cr
  • Plasma Physics and Fusion
    What you learn (7)
    • recall fundamental properties and parameters of plasmas
    • identify standard formulations used to describe different plasma regimes
    • describe scientific principles underlying applications of plasma physics
    • apply plasma physics principles to solve unfamiliar problems
    • use mathematical tools to analyse fusion-related plasma problems
    • evaluate current plasma research papers critically
    • relate research findings to core plasma science concepts
    PHY00049M 20 cr
  • 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
    PHY00052M 20 cr
  • Advanced Plasma Physics for Fusion and Applications
    What you learn (10)
    • distinguish different sources of transport in plasmas
    • determine the relative importance of transport mechanisms in given scenarios
    • analyse the relevance of plasma waves for technical applications such as heating
    • relate plasma instabilities to operational limits in fusion applications
    • compare different magnetic confinement schemes
    • explain electron and ion dynamics in low-temperature plasmas
    • discuss chemical kinetics in low-temperature plasmas
    • contrast low-temperature plasmas with fusion plasmas and their applications
    • explain why laser-plasma interactions produce a wide range of physical regimes
    • derive the fundamental equations governing laser-plasma interaction research
    PHY00053M 20 cr
  • 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
    PHY00055M 20 cr

“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, 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
MeasureValueBased on
Continue after year 17% left89%165
In work or study, 15 months on25% studying85%55
Professional or managerial job90%25
Pay 15 months on, median£34,00020
Pay 3 years on, median£30,000125
Pay 5 years on, median£37,500145
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 £50,250 in fees over 5 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 2025-26

What do students say?

83%agreed the course was good overall (question 26)

NSS — a yearly survey of final-year students at every UK university; 72% of this course’s final year answered. Small groups can swing a lot year to year.

National Student Survey, via Discover Uni · 115 students answered

Highest: 94% agreed on question 15; lowest: 52% on question 14.

All questions26
QuestionAgree
Question 188%
Question 279%
Question 391%
Question 488%
Question 580%
Question 685%
Question 786%
Question 884%
Question 989%
Question 1064%
Question 1182%
Question 1278%
Question 1379%
Question 1452%
Question 1594%
Question 1690%
Question 1774%
Question 1876%
Question 1989%
Question 2091%
Question 2188%
Question 2287%
Question 2376%
Question 2460%
Question 2565%
Question 2683%

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.