Applied Quantum Computing MSc - 2026/7
Awarding body
University of Surrey
Teaching institute
University of Surrey
Framework
FHEQ Levels 6 and 7
Final award and programme/pathway title
MSc Applied Quantum Computing
Subsidiary award(s)
Award | Title |
---|---|
PGDip | Applied Quantum Computing |
PGCert | Applied Quantum Computing |
Modes of study
Route code | Credits and ECTS Credits | |
Full-time | PGA61009 | 180 credits and 90 ECTS credits |
QAA Subject benchmark statement (if applicable)
Other internal and / or external reference points
N/A
Faculty and Department / School
Faculty of Engineering and Physical Sciences - Mathematics & Physics
Programme Leader
AL-KHALILI Jim (Maths & Phys)
Date of production/revision of spec
14/11/2024
Educational aims of the programme
- Analyze the impact of quantum computing on several different industries and domains (finance, chemistry, biology etc)
- Develop a solid understanding of the principles and foundations of quantum computing
- Explore quantum error correction and fault-tolerant quantum computing
- Explore quantum error correction and fault-tolerant quantum computing
- Explore the fundamental quantum algorithms and their applications
- Foster critical thinking and problem-solving skills specific to quantum computing
- Foster interdisciplinary collaboration and communication skills in quantum computing
- Gain practical experience in programming and simulating quantum circuits
- Prepare for future studies or careers in quantum computing and related fields
- Stay updated with the latest advancements and research in the field of quantum computing
- Understand the challenges and opportunities in quantum hardware development
Programme learning outcomes
Attributes Developed | Awards | Ref. | |
Communicate the fundamental principles and concepts of quantum mechanics that underpin a quantum computer through oral presentations, written reports, or other forms of documentation. | CPT | PGCert, PGDip, MSc | |
Apply quantum algorithms, such as Grover's algorithm and Shor's algorithm, to solve specific computational problems. | C | PGDip, MSc | |
Design and construct quantum circuits using quantum gates and understand their role in quantum computation. | C | PGCert, PGDip | |
Evaluate the strengths and weaknesses of different qubit hardware architectures for applications in quantum computing and communications. | C | PGCert, PGDip, MSc | |
Evaluate the strengths and, crucially, the limitations of quantum computers relative to classical computers for different potential applications. | C | PGCert, PGDip, MSc | |
Demonstrate proficiency in using quantum programming languages and tools for simulating and executing quantum algorithms. | KP | MSc | |
Understand and explain the importance of decoherence and quantum error correction for achieving reliable quantum computations. | KP | MSc | |
Critically evaluate the challenges in scaling up quantum computers and also the impact on opportunities for developing new codes. | C | PGCert, PGDip, MSc | |
Discuss the ethical and societal implications of quantum computing and its potential impact on human activity in communications, optimization, and simulation. | PT | MSc | |
Collaborate effectively in a team setting to design and implement quantum computing experiments or projects. | KCPT | PGCert, PGDip, MSc |
Attributes Developed
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
Programme structure
Full-time
This Master's Degree programme is studied full-time over one academic year, consisting of 180 credits at FHEQ level 7*. All modules are semester based and worth 15 credits with the exception of project, practice based and dissertation modules.
Possible exit awards include:
- Postgraduate Diploma (120 credits)
- Postgraduate Certificate (60 credits)
*some programmes may contain up to 30 credits at FHEQ level 6.
Programme Adjustments (if applicable)
N/A
Modules
Year 1 (full-time) - FHEQ Levels 6 and 7
Module Selection for Year 1 (full-time) - FHEQ Levels 6 and 7
September students undertake:
PHYM066 Introduction to quantum computing in semester 1
Then undertake the below compulsory modules in semester 1:
PHY3071 Applied Quantum Computing II (How to make a Qubit & Quantum Optimisation)
PHYM068 Superconducting Quantum Processors
Then select 1 from the below optional modules
PHYM067 Methods in Quantum Experiment and Simulation
LAWM161 Ethics and Regulation of AI
Then undertake the below compulsory modules in semester 2:
PHYM071 Quantum Algorithms
PHYM074 Applied Quantum Computing III (quantum biology & quantum information and decoherence).
PHYM075 Applied Quantum Computing IV (quantum communications & quantum simulation)
Then select 1 from the below optional modules in semester 2:
EEEM071 Advanced Topics in Computer Vision and Deep Learning
MATM063 Principles of Data Science
Then undertake the below compulsory module during the summer:
PHYM021 Research Project and Dissertation
February students undertake:
PHYM066 Introduction to Quantum Computing in semester 2 (your semester 1):
Then undertake the below compulsory modules in semester 2 (your semester 1):
PHYM075 Applied Quantum Computing IV (quantum communications & quantum simulation).
PHYM071 Quantum Algorithms
Then select 1 from the below optional modules in semester 2 (your semester 1):
EEEM071 Advanced Topics in Computer Vision and Deep Learning
MATM063 Principles of Data Science
Then undertake the below compulsory module during the summer:
PHYM021 Research Project and Dissertation
Then undertake the below compulsory modules in semester 1 (your semester 2):
PHYM068 Superconducting Quantum Processors
PHY3072 Applied Quantum Computing I (Finance and Quantum Mechanics).
PHY3071 Applied Quantum Computing II (How to make a Qubit & Quantum Optimisation)
Then select 1 from the below optional modules in semester 1 (your semester 2):
PHYM067 Methods in Quantum Experiment and Simulation
LAWM161 Ethics and Regulation of AI
Opportunities for placements / work related learning / collaborative activity
Associate Tutor(s) / Guest Speakers / Visiting Academics | Y | |
Professional Training Year (PTY) | N | |
Placement(s) (study or work that are not part of PTY) | N | |
Clinical Placement(s) (that are not part of the PTY scheme) | N | |
Study exchange (Level 5) | N | |
Dual degree | N |
Other information
Digital capabilities:
Quantum Computing (QC) obviously enhances Digital Capabilities directly, and this permeates the entire programme
Employability:
Employability is improved intrinsically in this programme by students gaining a unique skill set that is in demand by industry for ¿quantum readiness¿. Essentially, businesses understand that an information revolution is coming, but they do not understand how they might prepare for the disruption or take advantage of it, and they are looking for skilled staff.
o We will prepare students with skills of communication applied to quantum technology, the concepts of which are challenging to convey. This will be done e.g., by presentation of analysis of the latest developments in groups within the Quantum Communications half-module.
o We will provide (a limited number of competitively filled) summer semester Research Projects attached to companies such as Quantinuum, IBM etc. This will allow students to gain real placement experience, unlike many taught MSc¿s. We will also invite representatives of such companies to the student oral presentations associated with this project so that students that did not have the chance to do a placement can network with the placement providers too.
Global and cultural capabilities:
o We will continue with our practice established at UG and on other PGT programmes of mandatory EDI awareness workshops, embedded so that one compulsory module per semester cannot be passed without engagement with the material [Superconducting Quantum Processors and Quantum Computing Algorithms].
o An optional module of Law, Artificial Intelligence & Technology gives perspective on a global issue that has the potential to have significant implications, both positive and negative, across various legal systems and cultural contexts. This module will expose engineering and physical science students to legal frameworks related to AI and QT that could be applied in different countries with distinct cultural norms. By studying and analysing case studies and examples from around the world, students can develop a broader understanding of how AI and QT intersect with legal systems and the cultural nuances that shape its implementation and regulation.
o We will also introduce an element of ethics embedded (like the separate EDI workshops) in a compulsory (half-) module, Quantum Communications. QC, like AI, raises ethical and cultural questions to which the answers must come from a diverse set of cultures. For example, if quantum computing can be used for drug discovery, then bad actors could use it for bio-chemical weapons discovery. We will encourage students to critically analyse how quantum computing can impact individual rights, privacy, fairness, and accountability from a global perspective. Understanding and appreciating diverse ethical viewpoints can enhance students' cultural sensitivity and help them navigate the complex and very new ethical landscape produced by quantum computing in a global context.
Resourcefulness and resilience:
Through the collaborative learning experiences and group projects we will provide a trusting environment for students to student interactions, and through the guided seminars on latest research developments we will provide trusting environments for teacher student interactions, both of which will allow development of resourcefulness and resilience.
o Within the Introduction to Quantum Computing module we will require that students produce a self-evaluation of the weakest aspect of their skill and understanding (e.g. complex numbers, linear algebra, quantum mechanics etc), then research availability, choose, and complete a MOOC in that area. This will enhance self-reliance and resourcefulness by teaching students to reflect on their own areas of strength and weakness, and show them that they hold the power to change and grow in order to achieve their own educational and career goals and potential.
o The Programme comprises many types and instances of complex problem solving activity, especially in the Project, but also in smaller coursework projects in other modules. Through these activities students are encouraged to analyze the situation, identify possible solutions. This process of problem-solving fosters resilience as it requires students to persevere through setbacks. It encourages them to view obstacles as opportunities for growth and learning. Moreover, problem-solving cultivates self-reliance, empowering students to develop confidence in their ability to navigate and overcome difficulties independently. Students become better equipped to handle the uncertainties and demands of their academic and professional pursuits, ultimately preparing them for success in their future careers.
Sustainability:
QCs have potential to solve some kinds of problems more efficiently than classical computers, some with immense importance for sustainability. By facilitating more precise modelling and analysis, quantum computing can contribute to more sustainable practices, and students will gain an appreciation of how quantum technology more widely can lead to a greener world.
o The Quantum Optimization half-module focusses on complex optimization problems including logistics. Such problems apply for example to distribution and consumption in power grids, for example. By teaching students how QC programs can enable more efficient resource allocation, we show how they contribute to reducing energy waste and improving overall energy sustainability.
Quality assurance
The Regulations and Codes of Practice for taught programmes can be found at:
Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2026/7 academic year.