Digital Engineering Design (DED) covers the use of computers in all activities from the design to the manufacture of a product. It is at the forefront of information technology and of crucial importance to economies around the world. It is a vital part of many global industries including automotive, aerospace, oil, defence, finance and health.

This specialist option of the MSc Computational and Software Techniques in Engineering has been developed to reflect the wide application of DED and to deliver qualified engineers of the highest standard into industries operating in the fields of computational and software engineering.


  • Start dateSeptember
  • DurationOne year full-time, two-three years part-time
  • DeliveryTaught modules 40%, group project 20%, individual research project 40%
  • QualificationMSc
  • Study typeFull-time / Part-time
  • CampusCranfield campus

Who is it for?

Suitable for candidates from a broad range of engineering and applied mathematical backgrounds, including aeronautic, automotive, mechanical and electrical engineering, in addition to those with a mathematical and computational sciences training, who wish to both develop and complement their existing skill set in these important areas.

The specialist taught modules are designed to provide you with the knowledge, programming techniques and practical skills necessary to develop and use core CED solution software over a wide range of industrial settings.

Why this course?

Cranfield University is a leader in applied mathematics and computing applications. The CED option benefits from the knowledge and experience gained by the staff through their strong industrial links, particularly our well-established research collaborations with the petrochemical, automotive, aeronautical and financial sectors.

This course produces well-qualified graduates, ready to take on professional roles without additional training on the job. In recent years, key employers have requested a student visit to showcase their graduate roles.

This course is also available on a part-time basis, enabling you to combine studying alongside full-time employment. We are very well located for visiting part-time students from across the UK and Europe.

Informed by industry

This course is directed by an Industrial Advisory Panel who meet twice a year to ensure that it provides generic hands-on skills and up-to-date knowledge adaptable to the wide variety of applications that this field addresses.

A number of members also attend the annual student thesis presentations which take place at the end of July, a month or so before the end of the course. This provides a good opportunity to meet key employers.

The Industry Advisory Panel includes:

  • Black & Veatch Ltd,
  • Stone Rock Advisors,
  • Rolls-Royce,
  • Airbus,
  • Factset,
  • Cambridge Consultants,
  • Industrial Vision,
  • STFC,
  • Excelian,
  • SOLV3 Engineering Ltd,
  • Red Bull Technology,
  • L3 Harris,
  • Autonomous Devices,
  • Immense,
  • The Manufacturing Technology Centre.

Course details

You will complete a number of compulsory modules that are common across options, followed by specialist modules from your selected MSc option. In addition to the taught component, you will complete a group project and an individual research project. The course is delivered via a combination of structured lectures, tutorial sessions and computer-based workshops. A combination of mathematical, computational and hands-on use of industry-standard CED systems forms the basis of the specialist modules, covering the theory and application of CED-based software for the modelling, analysis and simulation.

Course delivery

Taught modules 40%, group project 20%, individual research project 40%

Group project

The process of software production is rarely an activity undertaken by an individual developer. In today’s software industry, many different specialists are required to contribute to the creation of software. To ensure a high level of quality in the final product, different roles and responsibilities must be brought together into a single team and therefore clear lines of communication between team members are crucial if the project is to be a success.

The group design project is intended to give you invaluable experience of delivering a project within an industry structured team. The project allows you to develop a range of skills including learning how to establish team member roles and responsibilities, project management, delivering technical presentations and gaining experience of working in teams that include members with a variety of expertise and often with members who are based remotely.

Part-time students are encouraged to participate in a group project as it provides a wealth of learning opportunities. However, an option of an individual dissertation is available if agreed with the Course Director.

Previous group projects have included:

  • Component stress analysis,
  • Steel tube joints flow study.

Individual project

The individual research project allows you to delve deeper into an area of specific interest. It is very common for industrial partners to put forward real world problems or areas of development as potential research project topics. For part-time students it is common that their research project is undertaken in collaboration with their place of work.

Previous individual research projects have included:

  • Analysis of aircraft control surface,
  • Comparative analysis of parallel performance and scalability of incompressible CFD solvers,
  • Automated workflow for a car roof-box optimisation,
  • Design optimisation of helical gear pair in helicopter transmission systems,
  • Design and analysis of an adjustable rear view car spoiler,
  • Surfboard modelling using CFD,
  • Displacement mapping using splines,
  • Aircraft fuel system failure detection.


Keeping our courses up-to-date and current requires constant innovation and change. The modules we offer reflect the needs of business and industry and the research interests of our staff and, as a result, may change or be withdrawn due to research developments, legislation changes or for a variety of other reasons. Changes may also be designed to improve the student learning experience or to respond to feedback from students, external examiners, accreditation bodies and industrial advisory panels.

To give you a taster, we have listed the compulsory and elective (where applicable) modules which are currently affiliated with this course. All modules are indicative only, and may be subject to change for your year of entry.

Course modules

Compulsory modules
All the modules in the following list need to be taken as part of this course.

Computational Methods


    The module aims to provide an understanding of a variety of computational methods for integration, solution of differential equations and solution of linear systems of equations.


    The module explores numerical integration methods; the numerical solution of differential equations using finite difference approximations including formulation, accuracy and stability; matrices and types of linear systems, direct elimination methods, conditioning and stability of solutions, iterative methods for the solution of linear systems.

Intended learning outcomes

On successful completion of this module you should be able to:

  • Formulate and assess numerical integration methods.
  • Use appropriate techniques to formulate numerical solutions to differential equations.
  • Evaluate properties of numerical methods for the solution of differential equations.
  • Choose and implement appropriate methods for solving differential equations.
  • Evaluate properties of systems of linear equations.
  • Choose and implement appropriate methods for solving systems of linear equations.
  • Assess the behaviour of the numerical methods and the computed numerical solutions.

C++ Programming

    Object oriented programming (OOP) is the standard programming methodology used in nearly all fields of major software construction today, including engineering and science and C++ is one of the most heavily employed languages. This module aims to answer the question ‘what is OOP’ and to provide the student with the understanding and skills necessary to write well designed and robust OO programs in C++. Students will learn how to write C++ code that solves problems in the field of computational engineering, particularly focusing on techniques for constructing and solving linear systems and differential equations. Hands-on programming sessions and assignment series of exercises form an essential part of the course. The library support provided for writing C++ programs using a functional programming approach will also be covered.   

    An introduction to the Python language is also provided.
    • The OOP methodology and method, Classes, abstraction and encapsulation
    • Destructors and memory management, Function and operator overloading, Inheritance and aggregation, Polymorphism and virtual functions, Stream input and output
    • Templates, Exception handling, The C++ Standard Library and STL
    • Functional programming in C++ 
Intended learning outcomes

On successful completion of this module you should be able to:

1. Apply the principles of the object oriented programming methodology - abstraction, encapsulation, inheritance and aggregation - when writing C++ programs.
2. Create robust C++ programs of simple to moderate complexity given a suitable specification.
3. Use the Standard Template Library and other third party class libraries to assist in the development of C++ programs.
4. Solve a range of numerical problems in computational engineering using C++.
5. Use development environments and associated software engineering tools to assist in the construction of robust C++ programs.
6. Evaluate existing C++ programs and assess their adherence to good OOP principles and practice.

Management for Technology

Module Leader
  • Dr Richard Adams
    The importance of technology leadership in driving the technical aspects of an organisation’s products, innovation, programmes, operations and strategy is paramount, especially in today’s turbulent commercial environment with its unprecedented pace of technological development. Demand for ever more complex products and services has become the norm. The challenge for today’s manager is to deal with uncertainty, to allow technological innovation and change to flourish but also to remain within planned parameters of performance. Many organisations engaged with technological innovation struggle to find engineers with the right skills. Specifically, engineers have extensive subject/discipline knowledge but do not understand management processes in organisational context. In addition, STEM graduates often lack interpersonal skills.
    • Engineers and Technologists in organisations:
      • the role of organisations and the challenges facing engineers and technologies,
    • People management:
      • understanding you, understanding other people, working in teams and dealing with conflicts.
    • The Business Environment:
      • understanding the business environment; identifying key trends and their implications for the organisation.
    • Strategy and Marketing:
      • developing effective strategies, focusing on the customer, building competitive advantage, the role of strategic assets.
    • Finance:
      • profit and loss accounts, balance sheets, cash flow forecasting, project appraisal.
    • New product development:
      • commercialising technology, market drivers, time to market, focusing technology, concerns.
    • Business game:
      • Working in teams (companies), you will set up and run a technology company and make decisions on investment, R&D funding, operations, marketing and sales strategy,
    • Negotiation:
      • preparation for negotiations, negotiation process, win-win solutions.
    • Presentation skills:
      • understanding your audience, focusing your message, successful presentations, getting your message across.

Intended learning outcomes

On successful completion of this module you should be able to:

  • Recognise the importance of teamwork in the performance and success of organisations with particular reference to commercialising technological innovation,
  • Operate as an effective team member, recognising the contribution of individuals within the team, and capable of developing team working skills in yourself and others to improve the overall performance of a team,
  • Compare and evaluate the impact of the key functional areas (strategy, marketing and finance) on the commercial performance of an organisation, relevant to the manufacture of a product or provision of a technical service,
  • Design and deliver an effective presentation that justifies and supports any decisions or recommendations made,
  • Argue and defend your judgements through constructive communication and negotiating skills.

Geometric Modelling and Design

    The aim of this module is to provide the student with the knowledge and practice of the mathematical techniques and the principal algorithms used for the construction of curve, surface and solid geometry. The module also addresses the geometric design factors impinging on the creation of CAD and other geometric models. The limitations and risk factors inherent in the choice of modelling approach are considered with respect to the surfacing technology used, current engineering data exchange standards and the implications for downstream applications such as finite element analysis. Case studies of CAD models used in the auto and other related industries are presented and the particular issues arising with respect to the above factors considered. Hands-on programming exercises and a modelling assignment form part of the course.
    Wireframe, surface and solid geometry, Polynomial and spline interpolation, B-spline curve and surface interpolation and approximation, Some advanced modelling techniques, Solid model representation schemes, Boundary representation models.
Intended learning outcomes

On successful completion of this module you should be able to:

  1. Solve a range of basic numerical problems in B-spline curve and surface data fitting and modelling.
  2. Apply B-spline curve and surface theory and algorithms to the construction of data fitting programs in a CAD modelling setting.
  3. Use the mathematical and computational techniques deployed in the creation of 3D geometric modelling software to extend existing implementations.
  4. Evaluate modern CAD systems in terms of established and newer/emerging surface modelling capabilities and their implications.

Computational Engineering Structures

    The module is aimed at giving potential Finite Element users basic understanding of the background of the method. The objective is to introduce users to the terminology, basic numerical and mathematical aspects of the method. This should help students to avoid some of the more common and important user errors, many of which stem from a "black box" approach to this technique. Some basic guidelines are also given on how to approach the modelling of structures using the Finite Element Method.
    Introduction to Finite Element Methods (FEM) and applicability to different situations 

    Introduction to the Direct Stiffness (Displacement) Method 

    Development of Truss, Bar Element Equations in 2D and 3D 

    Development of Beam and Frame Element Equations (2D and 3D) 

    Development of the Plane Stress element Equations (Constant and Linear Strain) 

    Accuracy considerations: higher order elements, Isoparametric elements.  

    The role of numerical integration and methods used in FE. 

    Practical Considerations in Modelling; Interpreting Results 
Intended learning outcomes

On successful completion of this module you should be able to:

Analyse and practice the theory of finite element models for structural and continuum elements.  

Design and solve mathematical finite element models.

Interpret results of the FE simulations and analyse error levels.

Create and solve mathematical finite element methods

Critically evaluate the constraints and implications imposed by the finite element method.

Digital Engineering and Product Design

    The aim of the module is to introduce students to key concepts, techniques and applications of a modern 3D Solid Modelling system. Use is made of structured computer based workshops which employ an industry standard system (CATIA) for 3D Solid Modelling. Introductory lectures are reinforced by the ‘hands-on’ approach through a series of part, assembly and surface modelling exercises covering the major workbenches available in the CAD system. A number of case studies and emerging modelling technologies are also covered.
    • Some benefits of using solid modelling and the CAE approach,
    • Different construction methods for 3D geometrical models,
    • Parametric and variational design,
    • Production of drafting setup details from 3D geometrical parts,
    • Modifying parts and features,
    • Case studies and advanced solid and surfacing tools and techniques
Intended learning outcomes

On successful completion of this module you should be able to:

1. Formulate solid geometrical parts and assemblies using a variety of fundamental CAD construction techniques including parametric and variational design.

2. Apply skills necessary to carry out a variety of Solid and Surface Modelling tasks.

3. Use appropriate drafting tools to generate 2D drawings from 3D geometrical parts.

4. Evaluate a modern CAE Solid Modelling package in terms of the range of solid and surface construction techniques offered.

5. Design CAD models of reasonable complexity from a given specification using a combination of part, assembly and surface modelling techniques

Computational Engineering Fluids

    To introduce the techniques and tools for modelling, simulating and analysing realistic computational engineering problems for industrial applications with practical hands on experience of commercial software packages used in industry. 
    • Introduction to Computational Engineering
    • Fundamental equations
    • The Computational Engineering Process
    • Fluid Simulation for Computer Graphics
    • Modelling techniques
    • Practical sessions
Intended learning outcomes

On successful completion of this module you should be able to:

Understand the Computational Engineering Process.

Understand the governing equations for fluid systems and how to solve them computationally.

Appreciate the wide range of applications using computational engineering for fluids.

Undertake pre-processing, processing and post processing techniques using a commercial code for physical fluid flow problems.



    Computer graphics is a key element in the effective presentation and manipulation of data in engineering software.  The aim of this module is to provide an in depth practical understanding of the mathematical and software principles behind 2D and 3D visualisation using the widely used OpenGL (desktop) and WebGL (web based) graphic libraries. Representative GUI based 2D and 3D OpenGL/WebGL applications using both Javascript/HTML5 and the Qt development environment are employed. The module will also cover some of the more advanced rendering techniques including lighting, texturing and other image mapping methods used to enhance visual interpretation of data. An introduction to the implementation and use of Virtual Reality in engineering completes the module. Hands-on exercises and an assignment supplement the learning process.

    • Mathematical principles behind 2D and 3D visualisation, The graphic and coordinate pipelines, Matrix transformations, Modelling, viewing and projection, OpenGL and WebGL libraries, GLSL shader programming.for the graphic pipeline and GPU
    • Development of interactive CG applications using OpenGL, WebGL, GLSL and Qt
    • Advanced rendering techniques, lighting, texturing and image mapping
    • Introduction to virtual reality.
Intended learning outcomes

On successful completion of this module you should be able to:

  • Apply the principles underlying the graphic and coordinate pipelines to display and manipulate 2D and 3D models.
  • Use the mathematical basis behind 2D/3D modelling and viewing to solve visualisation problems in OpenGL and WebGL.
  • Understand, implement and use GLSL shader programs for implementing the graphic pipeline.
  • Create interactive visualisation applications using OpenGL/ WebGL, GLSL and Qt.
  • Evaluate the use of VR and other advanced technologies for engineering visualisation.

Computational Optimisation Design

    The module aims to provide an understanding of optimisation theory and formulation of optimisation problems applied on engineering design. Understand the importance of the choice of suitable optimisation algorithms and complementary tools for geometry management and objective functions simulation and evaluation. Finally, to appreciate the importance of post-optimisation analysis and extraction of qualitative understanding of the relevant optimisation problems.
    Systems view of design optimisation in engineering 

    Optimisation theory and optimality criteria, single- and multi-objective 

    Deterministic and stochastic optimisation algorithms 

    Applied optimisation methodology 

    Post-optimisation analysis and visualisation 
Intended learning outcomes

On successful completion of this module you should be able to:

Evaluate the fundamental concepts of numerical and stochastic optimisation. 

Propose appropriate optimisation algorithms and formulate optimisation problems for a given engineering design study. 

Use scientific computational design tools with High Performance Computing. 

Integrate different computational analysis tools and methods within a computational design system. 

Perform assessment of an optimisation study with post-optimisation analysis and extract qualitative understanding of real-world design problems. 

Teaching team

Cranfield University is a leader in applied mathematics and computing applications, and you will be taught by experienced Cranfield staff including those listed below. Our staff are practitioners as well as tutors, with clients that include: Airbus, Conoco Phillips, Siemens and TATA Motors. Our teaching team works closely with business and has academic and industrial experience. Knowledge gained working with our clients and partners is continually fed back into the teaching programme, to ensure that you benefit from the very latest knowledge and techniques affecting industry. The course also includes visiting lecturers from industry and academia who will relate the theory to current best practice. In recent years, students on the DED option have received lectures from external speakers including: Dr Steve King, Rolls-Royce and Dr Terry Hewit, University of Manchester. The Course Director for this programme is Dr Stuart Barnes.

Your career

The Digital Engineering Design option is tailored to equip you with the skills required to pursue a successful career working both in the UK and overseas. This course attracts enquiries from companies in rapidly expanding engineering IT industry sector across the EU and beyond who wish to recruit high-quality graduates.

There is considerable demand for students with expertise in engineering software development and for those who have strong technical programming skills in industry standard languages and tools.

Typically our graduates are employed by software houses and consultancies or by CAD/CAM and other engineering companies in software development roles and industrial research.  

A selection of companies that have recruited our graduates include:

  • Design Manager, Hindustan Aeronautics Ltd,
  • Financial Software Developer, Bloomberg,
  • Research Engineer, Moodstocks SAS,
  • PLM Consultant, PCO Innovation,
  • Software Developer, CAE Engineering,
  • Computer Science Engineer, Sopra Group,
  • IT Architecture Consultant, Solucom,
  • Asset Management Engineering, EON UK,
  • Mathematical Software Engineer, Arithmetica Ltd,
  • Analyst, Morgan Stanley.

Cranfield’s Career Service is dedicated to helping you meet your career aspirations. You will have access to career coaching and advice, CV development, interview practice, access to hundreds of available jobs via our Symplicity platform and opportunities to meet recruiting employers at our careers fairs. Our strong reputation and links with potential employers provide you with outstanding opportunities to secure interesting jobs and develop successful careers. Support continues after graduation and as a Cranfield alumnus, you have free life-long access to a range of career resources to help you continue your education and enhance your career.

The reason why I wanted to come to Cranfield is because it's one of the best ranked schools. I really like coding and using computational tools to solve engineering problems. I think the course is really relevant and useful for today's digital era.
I applied for this course as I wanted to be more refined in the computer software field. Beyond the course, I can apply what I have learned in the modules, so that I can achieve a sense of accomplishment in my study. In addition, there are many choices in the topic of the thesis which combines interest and professionalism.
While studying civil engineering, I believed that digitalisation is the future of the construction industry and decided to pursue a MSc related to computer and machine vision. This Cranfield course offered me a valuable opportunity to learn the latest artificial intelligence techniques. This well-arranged modules, high-quality course content and industry-oriented research projects helped me develop fast. The timescale was intense but extremely exciting and very fulfilling. The fact that Cranfield is highly ranked guarantees the best education and research.

How to apply

Click on the ‘Apply now’ button below to start your online application.

See our Application guide for information on our application process and entry requirements.