MPhys (Hons) Physics with Artificial Intelligence Integrated Master's degree at the University of Leeds

Learn how to describe motion through physical space, forces and energies, coordinate systems. Study special relativity and motion at speeds approaching the speed of light. Learn to apply basic physical principles to objects in the Universe and explore the basics of radiation and observation.

Explore the underpinning theories and concepts of thermodynamics with examples and applications in sustainable energy.

Cover solid state and quantum physics including mechanics of solids, atomic structure, bonding, elasticity, photoelectric effect, Compton scattering, De Broglie relation, wave-particle duality, crystal structure and X-ray diffraction. Analyse and design simple electric circuits using resistors, capacitors and inductors. Learn Boolean algebra and digital logic design.

Learn about oscillators, energy and resonance, different types of waves, energy/power transfer, reflection and transmission, impedance, superposition and interference, wave-like behaviour of light, mirrors, lenses, nonlinear optics and lasers. Cover solution of 2nd order partial differential equations, complex numbers, Fourier series and introduction to Fourier transforms.

Develop practical experimental, computational, communication and employability skills through laboratory tasks and introduction to Python programming. Undertake tasks designed to improve teamwork, presentation skills and reflective practice.

Introduces key concepts in artificial intelligence (AI), exploring narrow AI and general AI. Gain insight into various classes of AI systems such as expert systems, neural networks, and reinforcement learning models. Emphasises how AI is transforming scientific fields including physics and chemistry, and highlights ethical considerations and limitations.

Introduce the physics behind nanotechnology in a semi-quantitative manner. Describe the physics of atoms and molecules, nano and bulk properties. Cover nanotechnological applications including nanomedicine.

Explore the multitude of planets being discovered around other stars and compare them to those in our solar system. Examine the origin and evolution of the solar system and extra-solar planets. Discuss conditions for life to emerge and prospects for finding life elsewhere.

Learn to describe quantum systems using wavefunctions, operators and linear algebra and predict outcomes of measurements on quantum systems. Solve the Schrodinger equation for simple model systems. Understand the structure of atoms and molecules using the exclusion principle and spin. Learn about the structure of the atomic nucleus, predict various forms of radioactive decay and nuclear reactions, describe scattering processes and understand key components of the Standard Model of particle physi

Explore the concepts and applications of statistical mechanics, key to understanding the behaviour of small-particle systems. Translate descriptions of physical problems and data analysis processes into short programs using a programming language to read and manipulate data, analyse and present results.

Learn about the use of the density of states to explain differences between metals, semiconductors and insulators. Derive the free-electron density of states, perform calculations based on free-electron theory and understand how a periodic potential modifies the free-electron dispersion relation. Solve problems on transport properties of semiconductors and calculate magnetic properties of paramagnets and ferromagnets. Build skills in communicating physics and research a topic whilst considering

Learn to use the integral versions of Maxwell's equations and calculate fields in cases of simple symmetric geometry. Calculate force and energy in electric and magnetic fields. Study Maxwell's equations in both integral and differential form. Analyse simple AC circuits containing resistors, capacitors and inductors. Apply logic principles to real-world scenarios in electronics and emerging technologies. Consider future career plans and complete CV, LinkedIn profile and job application forms.

Introduce basic techniques from statistical machine learning for classification and regression using Python. Cover areas like loss functions, optimisation, gradient descent, linear regression, logistic regression, support vector machines, decision trees, Bayesian learning and basic neural networks. Learn to assess the error of a fitted model and explain the fitting algorithm. Use software packages to perform classification and regression tasks and carry out simple statistical model analysis.

Further develops key computational experimental and research skills. Includes understanding the appropriate use of experimental and measuring equipment and computational techniques, drawing conclusions from results and understanding accuracy, critically analysing obtained data, and presenting results appropriately for different audiences.

Introduces the field of deep learning, giving practical skills and expertise to use neural networks to solve problems in science and engineering. Cover areas such as perceptron in Python, using Tensorflow/PyTorch, computation graphs, multilayer neural networks, using GPUs, hyperparameter tuning and convolutional neural networks. Understand fundamental concepts and methods of deep learning and its limitations. Critically evaluate systems using standard performance metrics and apply learned knowle

Offers students the opportunity to solve problems in physics through a series of short, focused projects. Projects cover diverse challenges such as using machine learning to analyse experimental data, optimising simulations of physical systems and developing AI models to identify patterns in complex datasets. Projects may explore areas like quantum mechanics, astrophysics and materials science. Emphasis on critical thinking, problem-solving and effective communication of results.

Study how quantum rules work and apply them to real situations. Use perturbation theory to study more complex and non-linear problems and understand how to study electron spins using Pauli matrices.

Study how the theory of phonons (lattice vibrations) can be used to study condensed matter and advanced semiconducting devices. Delve into the physics of nanoscale structures and introductory superconductivity.

An introduction to basic photonics, leading into the study of optical anisotropy, non-linear optics and lasers. Find out how to manipulate materials using optical tweazers.

Magnetic and ferroelectric materials underpin much of modern technology and everyday lives, from electric motors and dynamos to energy and data storage, sensors and computing. Shows the physics underpinning these materials and systems.