Students preparing for their graduation ceremony at Canterbury Cathedral

Engineering with Finance - MSc


The MSc in Engineering with Finance has been designed for engineering and science graduates who wish to pursue a career in finance. It is the first MSc in quantitative finance to be offered by a UK engineering department and provides a balanced mix of subjects in engineering and quantitative finance.



While a significant proportion of graduates working in the financial sector have an engineering background, most of the relevant MSc programmes are offered by Mathematics departments or Business Schools. Some engineers may find these programmes either too theoretical or not quantitative enough.

Our MSc in Engineering with Finance, instead, teaches concepts of finance at the level suitable to engineers, while also providing strong knowledge of quantitative methods to analyse real data. You acquire skills required by investment analysts, financial analysts, stockbrokers and market risk specialists.

The programme combines a balanced mix of subjects in engineering and quantitative finance, and is based on modules containing lectures, examples classes, directed self-study and PC-based laboratory classes. You acquire the skills required for a wide range of careers including investment analyst, financial analyst, stockbroker and market risk specialist.

About the School of Engineering and Digital Arts

The School successfully combines modern engineering and technology with the exciting field of digital media. Established over 40 years ago, the School has developed a top-quality teaching and research base, receiving excellent ratings in both research and teaching assessments.

We undertake high-quality research that has had significant national and international impact, and our spread of expertise allows us to respond rapidly to new developments. Our 30 academic staff and over 130 postgraduate students and research staff provide an ideal focus to effectively support a high level of research activity. There is a thriving student population studying for postgraduate degrees in a friendly and supportive teaching and research environment.

We have research funding from the Research Councils UK, European research programmes, a number of industrial and commercial companies and government agencies including the Ministry of Defence. Our Electronic Systems Design Centre and Digital Media Hub provide training and consultancy for a wide range of companies. Many of our research projects are collaborative, and we have well-developed links with institutions worldwide.

National ratings

In the Research Excellence Framework (REF) 2014, research by the School of Engineering and Digital Arts was ranked 21st in the UK for research intensity.

An impressive 98% of our research was judged to be of international quality and the School’s environment was judged to be conducive to supporting the development of research of international excellence.

Course structure

Our MSc in Engineering with Finance teaches concepts of finance at the level suitable to engineers on one hand, while providing strong knowledge of quantitative and computational methods to analyse real data, on the other.

Students acquire skills required in jobs such as investment analyst, financial analyst, stockbroker, market risk specialist etc. Previous students have applied for jobs in financial companies such as investment banks (eg Investec, Bank of New York Mellon), software trading platform developers (eg Murex) and management companies (eg Pentland Group plc). Advice about careers in the financial sector is provided and talks delivered by professionals are organised by the University.

This taught MSc course combines a balanced mix of subjects in engineering and quantitative finance, and is based on modules containing lectures, examples classes, directed self-study and PC-based laboratory classes.

Dr Gianluca Marcelli
Programme Chair 
Engineering with Finance

Student profiles

See what our students have to say.

Example projects

View examples of student projects for this course.


The following modules are indicative of those offered on this programme. This list is based on the current curriculum and may change year to year in response to new curriculum developments and innovation.  Most programmes will require you to study a combination of compulsory and optional modules. You may also have the option to take modules from other programmes so that you may customise your programme and explore other subject areas that interest you.

Possible modules may include Credits ECTS Credits

The module content will include:

• Statistical Concepts

• Probability Distributions

• Statistical Inference, Estimation and Hypothesis Testing

• Correlation, and General Dependence Measures

• Linear Regression

• Multiple Linear Regression

• Logistic Regression

• Monte Carlo Simulation

• Modelling in Excel

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Lecture Syllabus


Analysis of Bayesian Classification; Feature selection strategies using genetic algorithms and Principal Component Analysis; Multiple classifier combination strategies. Intelligent and dynamically adaptable classification techniques; Multi-source biometric systems and score normalisation techniques.



Four, six-hour assessed practical workshops.

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The aim of the module is to give the students a comprehensive introduction and overview of theoretical and practical aspects of financial econometrics. This module ensures that students have a solid foundation in statistical inference and econometrics with particular emphasis on the special features that are prevalent in quantitative finance.

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Lecture Syllabus


Introduction to signals and signal analysis. Frequency and time domain representations of signals. A review of the Fourier Series, Fourier Transform and Laplace Transforms. Noise: definitions and sources of noise in signal analysis.


The sampling theorem, Aliasing, Anti-Aliasing and Anti-Imaging Filters, ADCs and DACs. The Fourier Transform (FT). The Discrete Fourier Transform (DFT) and The Fast Fourier Transform (FFT).The Z-transform. Pole-Zero placement methods for signal analysis. Transfer functions in S and Z domains. Theory, design and performance of Finite Impulse-Response (FIR) and Infinite-Impulse-Response (IIR) Filters. Multirate DSP. Architectures and devices for digital signal processing. Effects of Finite Precision.


Processing and filtering of signals for Instrumentation and measurement, Processing and filtering of images: DSP in modern communication systems.



The six workshop assignments use MATLAB and SIMULINK to develop and explore concepts that have been introduced in the lectures.

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This course is concerned with the design of practical feedback controllers. Feedback is used in a control system to change the dynamics of the plant or process, and to reduce the sensitivity of the system to uncertainty from external signals (for example, disturbances and noise) and model uncertainty. If the performance specifications are achieved in the presence of the expected uncertainties, then the control is said to be robust.

Lecture Syllabus


Methods for modelling engineering processes, state space representation, controllability and observability. The feedback control paradigm.


Implications of digital implementation of feedback control systems. Controller Emulation Methods. Direct digital design of feedback control systems. Case study examples.


Characteristics of nonlinear system behaviour, Phase-plane methods, Variable-structure systems and sliding-mode control. Case study examples.



Digital control design, modelling and control fundamentals, nonlinear control techniques.


Advanced Control Systems


A real-life, open-ended control problem will be assigned to each student for suitable solution

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Lecture Syllabus

The lectures will provide an introduction to concepts of Finance and will consists of the following topics:

Financial markets

Financial institutions

Value, Return and Risk

Financial Analysis & Planning


Risk Management

This syllabus can change to reflect ongoing practice.


The module is 100% coursework and based on a group-project. Groups of 4-5 students will be given a real-world financial topic to research on. Students have to read relevant financial-journal articles, collect relevant financial data and applied mathematical models to propose analyses and forecasts. Tutorial classes will be used to present and discuss about relevant financial-journal articles and mathematical methods to be applied for group-projects.

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Lecture Syllabus


Introduces the basics of the Matlab and Simulink programming environment and prepares the students for the Introduction to Matlab workshops


Surveys using networked electronic information sources, on-line databases, inter-library loan facilities, private communications, etc. Identification of a technical area worthy of research, definition of the state-of -the-art in a given field, definition of the research project, and research proposals. Patent search.


Choosing the field of interest. Concept of originality. Research theories: background theory, focal theory, data theory. Contribution towards knowledge. Types of research project (blue sky, basic, applied and experimental research). Research uncertainty. Risk management. Research approaches.


Time management. Resources management. Project management software (MS Project). Use of logbooks. Data management. Data security. Team working skills.


MSc research projects. MPhil/PhD research projects. Academic research and industrial R&D. Project planning, proposals and budgeting. Design of experimental tests. Modelling and simulation.


Structure, content and procedures. Project reports and theses. Journal and conference papers. Technical presentations. Use of references. Writing up of abstract, introduction and conclusions. Submission, refereeing and amendments. Effective use of figures, drawings and tables. MS WORD, ENDNOTE and LATEX.


Objectives and structure. Audience analysis. Rehearsal and delivery. Design of visual aids. Use of computerized projection facilities. Multi-media approach. Poster design and poster presentation. Handling questions.


Patents, patent rights and know-how. Copyright and copying. Design rights and registered designs. Research contracts and agreements. Confidentiality agreement.


Ethics in engineering research. Research supervision. Modelling and simulation versus real experimental work. Processing and presentation of experimental data. Obfuscation in writing up research papers.


ASSIGNMENT – Literature Review (including patent research)

Two literature review reports are required. The first is a report on a common research topic given by the lecturer. The second report is on the student's own MSc project.

COMPUTER LABORATORY – Research Project Management

Two 2-hour laboratory sessions introducing and practising the use of MSc Project. The students will undertake a set of given tasks and submit a report.


The students will be required to write and submit a full project proposal prior to the start of their individual MSc project. The writing up skills will be tested in this assessed element.


The students will be required to produce a poster and make a poster presentation on their individual MSc project proposal.

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Lecture syllabus: 40 lectures (Spring Term)

Describe, perform calculations using and critically evaluate different measures of investment risk; critically evaluate the assumptions underlying the investment returns.

Describe, perform calculations using and discuss the assumptions of mean-variance portfolio theory and its principal results.

Describe utility functions, first and second order dominance, and perform calculations using commonly used utility functions to compare investment opportunities.

Describe, perform calculations using and discuss the concepts, construction and properties of single and multifactor models of asset returns.

Describe and perform calculations using asset pricing models, critically evaluating the principal results and assumptions and limitations of such models.

Discuss the various forms of the Efficient Markets Hypothesis and discuss the evidence for and against the hypothesis.

Demonstrate a knowledge and understanding of stochastic models of the behaviour of security prices and discuss the main theoretical and practical issues in setting up such models.

Define and apply the main concepts of Brownian motion (or Wiener Processes).

Demonstrate a good understanding of stochastic differential equations, the Ito integral, diffusion and mean-reverting processes and the Ornstein-Uhlenbeck process.

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A major practical system will be developed either in an industrial context or within the department. There are no formal lectures - students will undertake the work in their own time under the regular supervision of a member of the academic staff and, where appropriate, industrial collaborators.

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Teaching and Assessment

The project module is examined by a presentation and dissertation. The Research Methods and Project Design module is examined by several components of continuous assessment. The other modules are assessed by examinations and smaller components of continuous assessment. MSc students must gain credit from all the modules.

Programme aims

This programme aims to:

  • educate graduate engineers and equip them with practical and theoretical engineering- knowledge to prepare them for careers in the field of quantitative finance
  • provide you with a good understanding of a wide range of engineering methods applicable to financial problems
  • provide you with a specialised understanding of the principles and practices of engineering required by financial analysts and risk management professionals, or for further research work
  • provide you with proper academic guidance and welfare support
  • create an atmosphere of co-operation and partnership between staff and students, and offer you an environment where you can develop your potential
  • strengthen and expand opportunities for industrial collaboration with the School of Engineering and Digital Arts and the UK financial sector.

Learning outcomes

Knowledge and understanding

You gain knowledge and understanding of:

  • mathematical techniques used in engineering
  • engineering methods applied to quantitative finance
  • a range of programming tools
  • statistical theory and techniques
  • portfolio theory and risk management techniques
  • project management techniques

Intellectual skills

You develop intellectual skills in:

  • the ability to find the solution of technical problems using appropriately chosen mathematical models and methods
  • the ability to retrieve and analyse relevant finance information
  • the ability to apply financial-data analysis and forecast
  • the ability to evaluate and analyse financial problems and propose strategic solutions and predictions
  • the ability to analyse a problem and develop a system level specification, based on an understanding of the interaction between the component parts of the system
  • integration of information and data from a variety of sources to develop new computational tools for data analysis and forecast

Subject-specific skills

You gain subject-specific skills in:

  • the ability to analyse real-world financial problems and propose solutions and forecast
  • the ability to understand the fundamental principles and techniques used in quantitative finance.
  • the ability to describe and perform calculations, using principles of investment risk and portfolio theory
  • the ability to design and analyse robust control systems
  • the ability to understand the operation of advanced pattern classification techniques
  • the ability to apply management techniques to the execution of a project and to prepare technical reports and presentations
  • the ability to apply digital signal processing techniques for the interpretation of data

Transferable skills

You gain the following transferable skills:

  • the ability to generate, analyse, present and interpret data
  • use of information and communications technology and the  theory of statistics
  • personal and interpersonal skills, working as a member of a team
  • an ability to communicate effectively, in writing and verbally
  • the ability for critical thinking, reasoning and reflection
  • the ability to learn effectively for the purpose of continuing professional development.
  • the ability to manage time and resources within an individual and group project.


We have developed the programme with a number of industrial organisations, which means that successful students will be in a strong position to build a long-term career in this important discipline.

The School of Engineering and Digital Arts has an excellent record of student employability. We are committed to enhancing the employability of all our students, to equip you with the skills and knowledge to succeed in a competitive, fast-moving, knowledge-based economy.

Graduates who can show that they have developed transferable skills and valuable experience are better prepared to start their careers and are more attractive to potential employers. Within the School of Engineering and Digital Arts, you can develop the skills and capabilities that employers seek. These include problem solving, independent thought, report-writing, time management, leadership skills, team-working and good communication.

Kent has an excellent record for postgraduate employment: over 96% of our postgraduate students who graduated in 2015 found a job or further study opportunity within six months.

Building on Kent’s success as the region’s leading institution for student employability, we offer many opportunities for you to gain worthwhile experience and develop the specific skills and aptitudes that employers value.

Study support

Postgraduate resources

The School is well equipped with a wide range of laboratory and computing facilities and software packages for teaching and research support. There is a variety of hardware and software for image acquisition and processing, as well as extensive multimedia computing resources. The School has facilities for designing embedded systems using programmable logic and ASIC technology, supported by CAD tools and development software from international companies, including Cadence™, Xilinx™, Synopsys™, Altera™, National Instruments® and Mentor Graphics™. The SMT laboratory can be used for prototyping and small-volume PCB manufacture. A well-equipped instrumentation research laboratory is also available.

Students also have access to both commercial and in-house software tools for designing microwave, RF, optoelectronics and antenna systems (such as ADS™, CST™, HFSS™) and subsequent testing with network and spectrum analysers up to 110 GHz, an on-wafer prober, and high-quality anechoic chambers.


As a postgraduate student, you are part of a thriving research community and receive support through a wide-ranging programme of individual supervision, specialised research seminars, general skills training programmes, and general departmental colloquia, usually with external speakers. We encourage you to attend and present your work at major conferences, as well as taking part in our internal conference and seminar programmes.

Dynamic publishing culture

Staff publish regularly and widely in journals, conference proceedings and books. Recent contributions include: IEEE Transactions; IET Journals; Electronics Letters; Applied Physics; Computers in Human Behaviour.

Global Skills Award

All students registered for a taught Master's programme are eligible to apply for a place on our Global Skills Award Programme. The programme is designed to broaden your understanding of global issues and current affairs as well as to develop personal skills which will enhance your employability.  

Entry requirements

A 2.1 or higher honours degree in engineering, scientific, computing, or similar discipline, together with a sound background in maths. Programming skills and knowledge of basic statistics are desirable.

All applicants are considered on an individual basis and additional qualifications, and professional qualifications and experience will also be taken into account when considering applications. 

International students

Please see our International Student website for entry requirements by country and other relevant information for your country. 

Meet our staff in your country

For more advise about applying to Kent, you can meet our staff at a range of international events.

English language entry requirements

For detailed information see our English language requirements web pages. 

Please note that if you are required to meet an English language condition, we offer a number of pre-sessional courses in English for Academic Purposes through Kent International Pathways.

Research areas


The Group’s activities cover system and component technologies from microwave to terahertz frequencies. These include photonics, antennae and wireless components for a broad range of communication systems. The Group has extensive software research tools together with antenna anechoic chambers, network and spectrum analysers to millimetre wave frequencies and optical signal generation, processing and measurement facilities. Current research themes include:

  • photonic components
  • networks/wireless systems
  • microwave and millimetre-wave systems
  • antenna systems
  • radio-over-fibre systems
  • electromagnetic bandgaps and metamaterials
  • frequency selective surfaces.

Intelligent Interactions

The Intelligent Interactions group has interests in all aspects of information engineering and human-machine interactions. It was formed in 2014 by the merger of the Image and Information Research Group and the Digital Media Research Group.

The group has an international reputation for its work in a number of key application areas. These include: image processing and vision, pattern recognition, interaction design, social, ubiquitous and mobile computing with a range of applications in security and biometrics, healthcare, e-learning, computer games, digital film and animation.

  • Social and Affective Computing
  • Assistive Robotics and Human-Robot Interaction
  • Brain-Computer Interfaces
  • Mobile, Ubiquitous and Pervasive Computing
  • Sensor Networks and Data Analytics
  • Biometric and Forensic Technologies
    Behaviour Models for Security
  • Distributed Systems Security (Cloud Computing, Internet of Things)
  • Advanced Pattern Recognition (medical imaging, document and handwriting recognition, animal biometrics)
  • Computer Animation, Game Design and Game Technologies
  • Virtual and Augmented Reality
  • Digital Arts, Virtual Narratives.

Instrumentation, Control and Embedded Systems

The Instrumentation, Control and Embedded Systems Research Group comprises a mixture of highly experienced, young and vibrant academics working in three complementary research themes – embedded systems, instrumentation and control. The Group has established a major reputation in recent years for solving challenging scientific and technical problems across a range of industrial sectors, and has strong links with many European countries through EU-funded research programmes. The Group also has a history of industrial collaboration in the UK through Knowledge Transfer Partnerships.

The Group’s main expertise lies primarily in image processing, signal processing, embedded systems, optical sensors, neural networks, and systems on chip and advanced control. It is currently working in the following areas:

  • monitoring and characterisation of combustion flames
  • flow measurement of particulate solids
  • medical instrumentation
  • control of autonomous vehicles
  • control of time-delay systems
  • high-speed architectures for real-time image processing
  • novel signal processing architectures based on logarithmic arithmetic.

Staff research interests

Full details of staff research interests can be found on the School's website.

Professor John Batchelor: Professor of Antenna Technology

Design and modelling of multi-band antennas for personal, on-body and mobile communication systems; passive RFID tagging/sensing and skin mounted transfer tattoo tags; reduced-size frequency selective structures (FSS and EBG) for incorporation into smart buildings for control of radio spectrum.

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Dr Farzin Deravi: Reader in Information Engineering

Pattern recognition; information fusion; computer vision; image processing: image coding; fractals and self-similarity; biometrics; bio-signals; assistive technologies.

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Professor Michael Fairhurst: Professor of Computer Vision

Image analysis; computer vision; handwriting analysis; biometrics and security; novel classifier architectures; medical image analysis and diagnostics; document processing.

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Professor Steven Gao: Professor of RF/Microwave Engineering

Space antennas; smart antennas; microwave circuit and systems.

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Professor Nathan Gomes: Professor of Optical Fibre Communications

Optical-microwave interactions, especially fibreradio networks; optoelectronic devices and optical networks.

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Dr Richard Guest: Senior Lecturer & Deputy Head of School

Image processing; biometrics technologies including usability, cybermetric linkages and standardisation; automated analysis of handwritten data; document processing.

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Dr Sanaul Hoque: Lecturer in Secure Systems Engineering

Computer vision; OCR; biometrics; security and encryption; multi-expert fusion and document modelling.

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Dr Gareth Howells: Reader in Secure Electronic Systems

Biometric security and pattern classification techniques especially deriving encryption keys from operating characteristics of electronic circuits and systems.

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Dr Benito Sanz-Izquierdo: Lecturer in Electronic Systems

Antennas and microwaves.

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Dr Peter Lee: Senior Lecturer in Electronic Engineering

Embedded systems; programmable architectures; high-speed signal processing; VLSI/ASIC design; neural networks; optical sensor systems and applications; image processing using VLSI.

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Dr Gang Lu: Senior Lecturer in Electronic Instrumentation

Advanced combustion instrumentation; visionbased instrumentation systems; digital image processing; condition monitoring.

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Dr Gianluca Marcelli: Lecturer in Engineering

The understanding of complex systems, in particular, biological and financial systems; using mathematical modelling such as molecular simulation, Brownian dynamics and network theory.

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Mr Robert Oven: Senior Lecturer in Electronic Engineering

Modelling of ion implantation processes and ion diffusion into glass for integrated optic applications.

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Dr Konstantinos Sirlantzis: Senior Lecturer in Intelligent Systems

Pattern recognition; multiple classifier systems; artificial intelligence techniques; neural networks, genetic algorithms, and other biologically inspired computing paradigms; image processing; multimodal biometric models; handwriting recognition; numerical stochastic optimisation algorithms; nonlinear dynamics and chaos theory; Markov chain Monte Carlo (MCMC) methods for sensor data fusion.

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Dr Les Walczowski: Senior Lecturer in Electronic Engineering

The development of dynamic web applications, mobile applications and e-learning technology.

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Dr Chao Wang: Lecturer in Electronic Systems

Optical communications; microwave photonics; biophotonics.

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Professor Jiangzhou Wang: Professor of Telecommunications and Head of School

Modulation; coding; MIMO; mobile communications; wireless sensor networks. 

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Dr Xinggang Yan: Lecturer in Control Engineering

Nonlinear control; sliding mode control; decentralised control; fault detection and isolation.

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Professor Yong Yan: Professor of Electronic Instrumentation; Director of Research

Sensors; instrumentation; measurement; condition monitoring; digital signal processing; digital image processing; applications of artificial intelligence.

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Dr Paul Young: Senior Lecturer in Electronic Engineering

Design and modelling of microwave and millimetrewave devices and antennas, especially substrate integrated waveguides and smart antennas.

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The 2017/18 annual tuition fees for this programme are:

Engineering with Finance - MSc at Canterbury:
UK/EU Overseas
Full-time £9840 £17210
Part-time £4920 £8610

For students continuing on this programme fees will increase year on year by no more than RPI + 3% in each academic year of study except where regulated.*

The University will assess your fee status as part of the application process. If you are uncertain about your fee status you may wish to seek advice from UKCISA before applying.

General additional costs

Find out more about accommodation and living costs, plus general additional costs that you may pay when studying at Kent.


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