Physics with Artificial Intelligence (Industrial) BSc

Course overview

Physics is the most fundamental of all sciences, delving into the way the world around us works to provide technological advances and innovations for centuries.

From developing cancer treatments and artificial intelligence to answering the foundational questions of the universe, physics and physicists have had a significant impact across a variety of different industries – which is why it’s still such a sought-after and relevant discipline today.

Studying a physics degree at Leeds gives you the opportunity to delve into the fundamental laws of nature, building a solid foundation in core physics topics alongside experience in conducting your own project work based on current research areas – including a collaborative research project in your final year. Throughout your degree, you’ll have access to excellent facilities right here on campus, including laboratories and teaching spaces in the Sir William Henry Bragg Building.

This course is also highly flexible, with a range of optional and discovery modules to choose from so you can tailor the course to what interests you the most. Our close industry links and innovative research activity ensure our physics courses reflect the latest advancements and applications of the subject. You'll graduate with the specialist knowledge, skills, and experience necessary to launch a successful career in this highly valued profession, with a wide range of career options available to you.

Physics with AI: Shaping the Future of Science

Now, with the power of Artificial Intelligence (AI), the way we explore and innovate in physics is evolving faster than ever before.

At Leeds, we’re facing these innovations head on with this course.

This programme uniquely integrates core physics principles with cutting-edge AI and machine learning, equipping you with all the tools you’ll need to revolutionise this field.

Industrial placement year

This programme gives you the opportunity to undertake a paid industrial placement year as part of the course. Our close industry links give you the platform to apply to a number of major organisations such as Elder Studios Ltd, Vodafone Ltd and Renishaw.

Why study at Leeds:

• Our School’s globally-renowned research in quantum computing, theoretical astrophysics, and experimental physics will play a pivotal role in shaping this programme, ensuring that you’re learning the latest groundbreaking research at the intersection of physics and AI.

• Enhance your career prospects and give your CV that competitive edge before you graduate with a paid industrial placement year.

• Career Prospects: graduate with the relevant skills for careers in diverse fields, including data science and AI development, computational physics and scientific research, aerospace, telecommunications and energy industries, quantum technologies and materials science, finance and risk modelling.

• Access specialist facilities including laboratories and teaching spaces right here on campus.

• Get hands-on experience and put theory into practice through exciting project work.

Course details

We've designed this course to enable you to develop your physics knowledge, alongside the mathematical, computational and experimental methods that are needed to become qualified as a physicist.

As you move through the programme, you'll increasingly build on your solid foundation in physics to learn about and work on the latest developments in the subject, based on our research expertise. You’ll also cover topics such as ethics, philosophy and career options in physics.

We take a competency-based approach to assessment, to enable you to demonstrate your skills and knowledge across a range of activities.

Advanced AI techniques are integrated throughout giving you the tools to tackle complex scientific challenges through a combination of theoretical knowledge and practical application.

By combining a deep understanding of physics with cutting-edge AI expertise, this programme equips graduates with the interdisciplinary skills to excel in scientific research, industry, and emerging fields where AI and physics intersect.

From analysing vast datasets to enhancing simulations and automating experiments, AI transforms how physicists model, predict and interpret physical phenomena. You'll explore how machine learning and neural networks accelerate discoveries in quantum mechanics, astrophysics, and material science while improving the accuracy and efficiency of computational models.

AI also revolutionises data analysis in modern physics, enabling researchers to sift through massive datasets from large-scale experiments such as those at CERN or astronomical observatories. By applying AI techniques, you’ll develop the skills to identify anomalies, refine theoretical models, and extract valuable insights from complex data. Additionally, AI enhances experimental design by automating processes and optimising setups, allowing physicists to focus on analysis and innovation.

Course structure

The list shown below represents typical modules/components studied and may change from time to time. Read more in our terms and conditions.

For more information and a full list of typical modules available on this course, please read Physics with Artificial Intelligence (Industrial) BSc in the course catalogue

Years 1 and 2

Throughout your first two years, you'll gain knowledge and skills and learn how to apply them to solve problems across the fundamental areas of physics including: electrodynamics, thermal physics, classical mechanics, quantum physics, solid state physics, waves, optics, contemporary physics and physics for sustainable development. Computer programming is an integral part of physics, and during the first two years you'll be taught the programming skills that you need, using Python.

Year 1 compulsory modules

Mechanics, Relativity and Astrophysics – 20 credits

In mechanics, you’ll learn how to describe motion through physical space, together with the general causes of that motion: forces and energies. You'll also learn about using appropriate co-ordinate systems and the synergies between linear and circular motions. You’ll develop the mathematical skills to describe mechanical processes, including vectors, unit vectors, scalar and vector products, calculus and summations. In special relativity, you'll extend your knowledge of co-ordinate systems to study motion as it appears to observers moving at different speeds. You'll also cover the theories originally developed by Einstein to describe this motion at speeds approaching the speed of light, and how the forces and energies of classical mechanics extend into the regime. In Astrophysics, you'll learn how to apply basic physical principles to objects in the Universe and explore the basics of radiation and how we observe these phenomena.

Thermodynamics – 20 credits

Explore the underpinning theories and concepts of thermodynamics. Examples and applications will be used to allow you to build your understanding and application of this branch of physics, including in sustainable energy, which governs the behaviour of the universe we live in.

Electronics, Solid State and Introduction to Quantum Physics – 20 credits

In solid state and quantum physics, you’ll cover the 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.

In addition, you’ll analyse and design simple electric circuits using fundamental circuit elements, such as resistors, capacitors and inductors.

You’ll also learn the principles of Boolean algebra and its application in digital logic design.

Vibrations, Waves and Optics – 20 credits

Vibrations and waves are ubiquitous phenomena, occurring in widely different physical systems, from molecules to musical instruments to tectonic plates. Nevertheless, they can be described by a common mathematical approach, which this module provides.

In vibrations and waves, you’ll 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.

Coding and Experimental Physics – 20 credits

Develop practical experimental, computational, communication and employability skills. You’ll build experimental skills through a range of laboratory tasks undertaken throughout the year and be introduced to programming using the Python computer programming language. You’ll also undertake tasks and assessments designed to improve your teamwork and presentation skills, as well as reflective practice. 

Applications of Artificial Intelligence – 10 credits

This module introduces key concepts in artificial intelligence (AI), exploring the differences between narrow AI, which excels at specific tasks, and general AI, which aims to replicate human-like cognitive abilities.

Through real-world examples from scientific applications, you’ll gain insight into the various classes of AI systems, such as expert systems, neural networks, and reinforcement learning models. The module emphasises how AI is transforming scientific fields, including physics and chemistry, and highlights the ethical considerations and limitations associated with AI technologies.

By the end of the module, you’ll have a foundational understanding of AI systems and their applications across science.

Optional modules

You’ll choose one of the following optional modules.

Please note: The modules listed below are indicative of typical options.

Introduction into Python for Machine Learning – 10 credits

Gain the foundations to understand and use one of the most popular programming languages used in Machine Learning/AI. Throughout the module, you’ll develop a good understanding of how Python works and be able to use it to write a program that can solve scientific problems. You may cover topics such as control structures, data types and data structures to implementing machine learning algorithms and importing and using libraries. You’ll also learn how to access data from the web or databases and graphically display that data.

Introduction to Nanotechnology – 10 credits

The smallest possible devices that can be fabricated are on the nanometre length scale. Miniaturisation of devices offers many new technological opportunities, which are only just starting to be implemented in our lives. The physical properties of nanomaterials differ from both the constituent atoms and the bulk material. These can be unique and surprising. This module aims to introduce the physics behind nanotechnology in a semi-quantitative manner, without requiring knowledge of quantum mechanics or Maxwell’s equations. To understand nanotechnology, we will describe the physics of atoms and molecules, before moving on to discuss nano and bulk properties. We will cover a number of nanotechnological applications currently adopted and on the horizon, including nanomedicine.

Planets and the Search for Life – 10 credits

Explore the multitude of planets that are currently being discovered around other stars and compare them to those in our solar system. This module will concentrate on the concepts involved and is non-mathematical, and therefore amenable to students of the arts, humanities and sciences. We will examine the origin and evolution of the solar system and how it is likely to have produced the range of planets, moons and minor bodies that we see today. This will be contrasted with the range of extra-solar planets, their detection, properties, and how they challenge our understanding of how planets are formed. Finally, the conditions for life to emerge will be discussed and the prospects and techniques for finding life elsewhere in the solar system and on exo-planets will be explored.

Year 2 compulsory modules

Quantum Mechanics – 20 credits

Learn how to describe quantum systems using wavefunctions, operators and linear algebra and how to predict outcomes of measurements on quantum systems. You’ll also learn to solve the Schrodinger equation for simple model systems and understand the structure of atoms and molecules using the exclusion principle and spin. In addition, you’ll 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 the key components of the Standard Model of particle physics.

Statistical Mechanics and Computation – 20 credits

Explore the concepts and applications of statistical mechanics, which are key to understanding the behaviour of small-particle systems. This module will also enable you to 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.

Condensed Matter Physics – 20 credits

During this module, you’ll learn about the use of the density of states to explain some of the differences between metals, semiconductors and insulators. You’ll also 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 (consistent with the syllabus) of paramagnets and ferromagnets. You’ll also build skills in communicating physics in preparation for projects/dissertations and research a topic of physics and communicate it in various formats whilst considering the importance of professional ethics and scientific conduct.

Electromagnetism – 20 credits

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, Maxwell's equations in both integral and differential form and discuss their derivation from the physical laws of electromagnetism. You’ll analyse simple AC circuits containing resistors, capacitors and inductors and apply logic principles to real-world scenarios in electronics and emerging technologies, developing the knowledge and skills needed to navigate the evolving landscape of electronic systems, from classical to quantum. As part of this module, you’ll also consider future career plans and complete a CV, LinkedIn profile and job application forms.

Machine Learning Fundamentals with Applications in Science and Engineering – 20 credits

We'll introduce basic techniques from statistical machine learning for classification and regression using Python. Throughout the module, you may cover areas like loss functions, optimisation, gradient decent, linear regression, logistic regression, support vector machines, decision trees, Bayesian learning and basic neural networks.

You could also learn how to assess the error of a fitted model and explain the fitting algorithm. You’ll also use software packages to perform classification and regression tasks, as well as carrying out a simple statistical model analysis of data in science and engineering.

Experimental Skills for Physics with Artificial Intelligence – 20 credits

This module further develops key computational experimental and research skills. This includes understanding the appropriate use of experimental and measuring equipment and computational techniques, being able to draw conclusions from results obtained as well as 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.

Year 3

You’ll have the opportunity to apply to spend a year in industry. A work placement is an invaluable opportunity to transfer your learning into a practical setting, applying the knowledge and skills you’ve been taught throughout your degree to real-world challenges – in a working environment. It’s important to note, work placements are not guaranteed.

Year 4

In your final year, your work will be closely linked to our current research, conducting your own research project. You’ll also have chance to choose from a range of specialist optional module topics.

Compulsory modules

BSc Research Project – 40 credits

This module offers you hands-on experience in the cutting-edge research. You’ll undertake an independent research programme, under the supervision of one or more members of staff within one of the existing research groups of the School. This will involve the preparation, planning and delivery of a programme of research (experimental/ computing/ theoretical/ education) in Physics or a related discipline under the guidance of the supervisor. Carry out some analysis of data from the literature or new data generated during the project. Your project will include an AI element by leveraging combinations of computational techniques, algorithms and advanced software tools to explore or control complex physical systems. This module not only enhances your research skills but also encourages innovation in applying AI methodologies to address real-world challenges in areas such as quantum mechanics, astrophysics, materials science, healthcare and biophysics and computational fluid dynamics.

Advanced Topics in Physics – 40 credits

Develop a broad knowledge, understanding and application of core areas in advanced physics and be able to solve unseen, problem-led questions in these areas. You’ll study options drawn from advanced quantum mechanics, condensed matter, bionanophysics, advanced classical mechanics, optics and star and planet formation.

Deep Learning Fundamentals with Applications in Science and Engineering – 20 credits

The module introduces the field of deep learning, giving you the practical skills and expertise to use neural networks to solve problems in science and engineering. Throughout this module, you may cover areas such as cover perceptron in Python, using Tensorflow/PyTorch, computation graphs, multilayer neural networks, using GPU’s, hyperparameter tuning and convolutional neural networks. Once you’ve finished the module, you’ll understand fundamental concepts and methods of deep learning – and its current limitations. You’ll also be able to critically evaluate systems using standard performance metrics and apply your learned knowledge to solve real-world scientific or engineering problems.

Optional modules

As we're currently reviewing the curriculum, specific optional modules have not been confirmed for 2026 entry.

The topics listed below are indicative of typical options we currently offer within the School, but some of these options may not be available or may be subject to change, and other options may be offered in their place.

Topic examples:

• Cosmology

• Theoretical Particle Physics

• Quantum Photonics

• Magnetism in Condensed Matter

• Molecular Simulation: Theory and Practice

Summer internships

As a student in our Faculty, you’ll have the unique opportunity to do a paid summer internship. It’s your chance to get involved in the real-world research projects happening in and around the University – and advance your own professional skills in research and experimentation.

Want to find out more? Check out what our recent students got up to on their summer internships.

Learning and teaching

On this course, you’ll be taught by our expert academics, from lecturers through to professors. You may also be taught by industry professionals with years of experience, as well as trained postgraduate researchers, connecting you to some of the brightest minds on campus.

Entry requirements

A-level: AAA including Physics and Mathematics

Where an A Level science subject is taken, we require a pass in the practical science element, alongside the achievement of the A Level at the stated grade.

Extended Project Qualification (EPQ), International Project Qualification (IPQ): We recognise the value of these qualifications and the effort and enthusiasm that applicants put into them, and where an applicant offers an A in the EPQ, IPQ or ASCC we may make an offer of AAB at A-level including A in Physics and Mathematics.

GCSE: English Language grade 4 (C) or higher, or an equivalent English language qualification. We will accept Level 2 Functional Skills English instead of GCSE English.

Alternative qualification

Alternative entry

We’re committed to identifying the best possible applicants, regardless of personal circumstances or background.

Access to Leeds is a contextual admissions scheme which accepts applications from individuals who might be from low income households, in the first generation of their immediate family to apply to higher education, or have had their studies disrupted.

If you live in a neighbourhood where there is low participation in higher education, we may be able to give priority to your application.

Find out more about Access to Leeds and contextual admissions.

Alternative Entry Scheme for Mature Students

If you are a mature applicant (over 21) and you don’t have the required A Levels or GCSE English and maths qualifications, you can complete our Alternative Entry Scheme (subject to meeting the eligibility criteria for the scheme). As part of this, you may be asked to take tests in English and maths and to write an essay.

Further information on the support available for mature students can be found here.

International Foundation Year

International students who do not meet the academic requirements for undergraduate study may be able to study the University of Leeds International Foundation Year. This gives you the opportunity to study on campus, be taught by University of Leeds academics and progress onto a wide range of Leeds undergraduate courses. Find out more about International Foundation Year programmes.

English language requirements

IELTS 6.0 overall, with no less than 5.5 in any one component. For other English qualifications, read English language equivalent qualifications.

Improve your English
If you're an international student and you don't meet the English language requirements for this programme, you may be able to study our undergraduate pre-sessional English course, to help improve your English language level.

Fees

UK: To be confirmed

International: To be confirmed

Tuition fees for UK undergraduate students starting in 2025/26
The fee for UK undergraduate students is decided by the Government and may vary if policy changes. The fee may increase in future years of your course in line with inflation, and as permitted by law.

Tuition fees for UK undergraduate students starting in 2025/26 will be £9,535.

The tuition fee for the following programmes with an integrated foundation year is £5,760 for the foundation year, and £9,535 for subsequent years of study:
•    Business Studies with Foundation Year BSC
•    Arts and Humanities with Foundation Year BA
•    Interdisciplinary Studies with Preparation for Higher Education BA
•    Social Science (foundation year) BA
 

Tuition fees for international undergraduate students starting in 2025/26
Tuition fees for international students for 2025/26 are available on individual course pages.
 

Tuition fees for a study abroad or work placement year
If you take a study abroad or work placement year, you’ll pay a reduced tuition fee during this period. For more information, see Study abroad and work placement tuition fees and loans.

Read more about paying fees and charges.

There may be additional costs related to your course or programme of study, or related to being a student at the University of Leeds. Read more on our living costs and budgeting page.

Scholarships and financial support

If you have the talent and drive, we want you to be able to study with us, whatever your financial circumstances. There is help for students in the form of loans and non-repayable grants from the University and from the government. Find out more in our Undergraduate funding overview.

Applying

Apply to this course through UCAS. Check the deadline for applications on the UCAS website.

Admissions policy

University of Leeds Admissions Policy 2025

This course is taught by

School of Physics and Astronomy

Contact us

Email:
Telephone:

Career opportunities

There are extensive employment opportunities in the field of physics across numerous industries, which is why physics graduates are in demand for some of the highest paid and most satisfying roles in employment.

Plus, University of Leeds students are among the top 5 most targeted by top employers according to The Graduate Market 2024, High Fliers Research, meaning our graduates are highly sought after by some of the most reputable companies in the field.

The skills and knowledge you’ll develop on this programme in both AI and chemistry will equip you with these industrially-relevant expertise, and will provide career opportunities in a variety of roles across a wide range of sectors, including:

• Data science and AI development

• Computational physics and scientific research

• Aerospace, telecommunications, and energy industries

• Quantum technologies and materials science

• Finance and risk modelling

Careers support

At Leeds, we help you to prepare for your future from day one. We have a wide range of careers resources — including our award-winning Employability Team who are in contact with many employers around the country and advertise placements and jobs. They are also on hand to provide guidance and support, ensuring you are prepared to take your next steps after graduation and get you where you want to be.

• Employability events — we run a full range of events including careers fairs in specialist areas and across broader industries — all with employers who are actively recruiting for roles.

• MyCareer system — on your course and after you graduate, you’ll have access to a dedicated careers portal where you can book appointments with our team, get information on careers and see job vacancies and upcoming events.

• Qualified careers consultants — gain guidance, support and information to help you choose a career path. You’ll have access to 1-2-1 meetings and events to learn how to find employers to target, write your CV and cover letter, research before interviews and brush up on your interview skills.

• Opportunities at Leeds — there are plenty of exciting opportunities offered by our Leeds University Union, including volunteering and over 300 clubs and societies to get involved in.

We’re also an active partner in the White Rose Industrial Physics Academy, where we hold the UK’s largest annual Physics Careers Fair, with employers looking exclusively for physicists.

Explore more about your employability opportunities at the University of Leeds.

We encourage you to prepare for your career from day one. That’s one of the reasons Leeds graduates are so sought after by employers.

The Careers Centre and staff in your faculty provide a range of help and advice to help you plan your career and make well-informed decisions along the way, even after you graduate. Find out more about Careers support.