BSc (Hons) Physics with Artificial Intelligence (Industrial) Bachelor's degree at the University of Leeds

Learn how to describe motion through physical space, forces and energies, coordinate systems, linear and circular motions, mathematical skills including vectors, unit vectors, scalar and vector products, calculus and summations. Extend knowledge to special relativity and motion at speeds approaching the speed of light. Learn how to apply basic physical principles to objects in the Universe and explore the basics of radiation.

Explore the underpinning theories and concepts of thermodynamics with examples and applications including sustainable energy, governing the behaviour of the universe.

Cover underpinning theories and concepts including mechanics of solids, Bohr atom, atomic electron states, elementary 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 its application in digital logic design.

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

Develop practical experimental, computational, communication and employability skills through a range of laboratory tasks undertaken throughout the year and introduction to programming using Python. Undertake tasks and assessments designed to improve teamwork, presentation skills, and reflective practice.

Introduces key concepts in artificial intelligence (AI), exploring the differences between 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 the ethical considerations and limitations associated with AI technologies.

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

Explore the multitude of planets currently being discovered around other stars and compare them to those in our solar system. Examine the origin and evolution of the solar system, the range of extra-solar planets, their detection and properties. Discuss the conditions for life to emerge and the prospects and techniques for finding life elsewhere in the solar system and on exo-planets.

Learn how to describe quantum systems using wavefunctions, operators and linear algebra and how to predict outcomes of measurements on quantum systems. Learn to solve the Schrodinger equation for simple model systems and 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 between elementary particles and understand th

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

Learn about the use of the density of states to explain some of the differences between metals, semiconductors and insulators. Cover how to derive the free-electron density of states, perform straight-forward calculations based on the free-electron theory and how a periodic potential modifies the free-electron dispersion relation, solving problems on the transport properties of semiconductors, and calculating the magnetic properties of paramagnets and ferromagnets. Build skills in communicating

Learn how to use the integral versions of Maxwell's equations and to calculate fields in cases of simple symmetric geometry, calculate the force and energy in electric and magnetic fields. Learn Maxwell's equations in both integral and differential form and discuss their derivation from the physical laws of electromagnetism. Analyse simple AC circuits containing resistors, capacitors and inductors and apply logic principles to real-world scenarios in electronics and emerging technologies. Consid

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 how to assess the error of a fitted model and explain the fitting algorithm. Use software packages to perform classification and regression tasks, as well as carrying out a simple statistical mo

Further develops key computational experimental and research skills. Includes understanding the appropriate use of experimental and measuring equipment and computational techniques, being able to draw conclusions from results obtained and understand the accuracy of those results to critically analyse the obtained data, as well as presenting those results in an appropriate fashion for different audiences.

Offers hand-on research experience. In your final year, your work will be closely linked to our current research, conducting your own research project.