With the advent of ever more sophisticated and powerful computer environments, the techniques needed to develop and produce the software to run on these systems are themselves becoming increasingly complex. This course is unique in that it combines software engineering with high performance computing, giving you the tools and techniques that employers are looking for and an advantage in the job market.

This specialist option of the MSc Computational and Software Techniques in Engineering offers a unique insight into the development of computer applications across a wide spectrum of modern computing environments, from multi-core CPUs to specialist GPUs to Cloud Computing, all of which are relevant to the IT industry today.

At a glance

  • Start dateSeptember
  • DurationOne year full-time, two-three years part-time
  • DeliveryTaught modules 45%, Group project 5%, Individual research project 50%
  • QualificationMSc
  • Study typeFull-time / Part-time

Who is it for?

If you intend to make a career in software development, whether it is in the data centre, on the desktop or in the rapidly expanding mobile application space, you need to have a strong basis in software engineering. This course is unique in that it combines software engineering with high performance computing, giving you the tools and techniques that employers are looking for and an advantage in the job market.

Why this course?

Cranfield University has many years of specialist knowledge and experience in High Performance Computing. We are able to offer a unique insight into the development of computer applications across a wide spectrum of modern computing environments, from multi-core CPUs to specialist GPUs to Cloud Computing, all of which are relevant to the IT industry today.

We introduce students to parallel software development on the desktop, the super-computer and in the Cloud. Each platform has its own challenges and this course ensure that students become familiar with the best approach to writing software for each one.

Cranfield University is very well located for visiting part-time students from all over the world, and offers a range of library and support facilities to support your studies.  This enables students from all over the world to complete this qualification whilst balancing work/life commitments. Part-time students have a flexible commencement date.

This Msc programme benefits from a wide range of cultural backgrounds which significantly enhances the learning experience for both staff and students

Informed by Industry

The course is directed by an Industrial Advisory Panel that meets twice a year. The committee acts in an advisory role, assessing the content of the course and its relevance to present industrial needs. 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.

The Industry Advisory Panel includes:

  • Dr Peter Grandison, IBM (UK) Ltd.
  • Mr Nigel Sedgwick, Cambridge Algorithmica.
  • Dr Derek Turnbull, Advanced Technical Projects Ltd.
  • Mr David Harrison, Cray Research (UK) Ltd
  • Mr Tim Penhale-Jones, Texas Instruments Ltd
  • Dr Richard Burguete, Airbus UK
  • Prof David Emerson  (Scientific Computing, STFC Daresbury )
  • Dr Stuart Barnes (Software Engineer, Cambridge).

Your teaching team

Cranfield University is a leader in applies mathematics and computing applications.  You will be taught by Cranfield's leading academic staff including:

Our teaching team work closely with business and have academic and industrial experience. Knowledge gained working with our clients 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 who will relate the theory to current best practice. In recent years, our students have received lectures from industry speakers including:

  • Richard Stewart, FACTSET
  • Dan Nelson, OCADO
  • Adam Vile, Excelian.

Course details

The course consists of twelve core modules, including a group design project, plus an individual research project. The course is delivered via a combination of structured lectures, tutorial sessions and computer based workshops.

The C++ and Java programming modules, combined with the Software Engineering course, provide the basis of the academic programme and act as a starting point for the more specialist modules encountered later on. The various computational technology platforms are then introduced, giving students both theoretical and hands-on experience of programming in multi-core, General Purpose CPU, distributed and Cloud computing environments.

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.

An important part of this MSc course is the group project, in which we define a realistic problem and ask each group to propose and implement a solution. It is generally a 6 week project taking place between February and March. Members of each group must decide how to organise themselves, assigning roles to each person.

The group project is an opportunity for you to experience first-hand how a software development team is organised and how the different roles contribute to the final product. This is a chance for you to develop an insight into the organisation of development teams in industry, and allows you to understand what is expected from you once you enter employment.

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:

  • Scientific Workflows
  • Security considerations for distributed computing applications
  • Automated recovery mechanisms for design optimisation.

Individual project

The individual research project allows you to delve deeper into an area of specific interest. All projects are based on real research, whether it is an area of interest for members of the department, or as part of an active research project funded by industry. In some cases our industrial partners sponsor specific research projects into real world problems or areas of development that are of direct interest to them. In recent years, students have proposed their own ideas for their research project. You will generally begin to consider the research project after completing 3-4 modules - it then runs concurrently with the rest of your work.

For part-time students it is common that their research thesis is undertaken in collaboration with their place of work.

Previous Individual Research Projects have included:

  • Using Twitter to Predict Financial Market Sentiment.
  • Visualisation of Source Code and Defects
  • Android Based Monitoring of Hybrid Car Engines
  • Development of Mutation Analysis Tool for PHP Software
  • Time-dependent Augmented Reality Visualisation on a Mobile Device
  • Analysis of Concurrency in CUDA Based Applications
  • Development of Domain Specific Language for CUDA Development
  • Automated Data Flow Checking Tool Development.

Assessment

Taught modules 45%, Group project 5%, Individual research project 50%

University Disclaimer

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 core modules and some optional modules affiliated with this programme which ran in the academic year 2017–2018. There is no guarantee that these modules will run for 2018 entry. All modules are subject to change depending on your year of entry.

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

C Programming (pre-requisite)

Module Leader
Aim

    The module aims to cover all the main elements making up the C programming language and to provide many illustrative examples of their use in practice. Use is made of ‘hands-on’ workshops which enable the student to gain confidence with the language and form a preparation for the practical assignment which forms a major part of the course. An Ansi-standard C compiler and development environment is employed.

Syllabus
    • Variables, operators and expressions
    • Statements and flow control
    • Functions
    • Pointers and arrays
    • Strings
    • Structures and other derived types
    • Dynamic memory
    • Allocation
    • Input and output.
Intended learning outcomes

On completion of this module the student will be able to:

  • Demonstrate a good understanding of the main elements making up a procedural language
  • Use functions, pointers and structures in the C language
  • Write a C program of moderate complexity given a formal specification
  • Understand the concept of dynamic memory allocation and be able to use it in practical applications
  • Apply knowledge and skills to the implementation of advanced data structures in the C language.

Computational Methods

Module Leader
  • Dr Irene Moulitsas
Aim

    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.

Syllabus

    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.

Intended learning outcomes On successful completion of this module a student should be able to:
1. Implement and use numerical integration methods.
2. Use appropriate techniques to formulate numerical solutions to differential equations.
3. Evaluate properties of numerical methods for the solution of differential equations.
4. Choose and implement appropriate methods for solving differential equations.
5. Evaluate properties of systems of linear equations.
6. Choose and implement appropriate methods for solving systems of linear equations.
7. Evaluate the behaviour of the numerical methods and the numerical solutions.

C++ Programming

Module Leader
  • Dr Irene Moulitsas
Aim

    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.

Syllabus
    • 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.
Intended learning outcomes

On completion of this module the student will be able to:

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

Computer Graphics Occ B (ESTIA)

Module Leader
  • Dr Karl Jenkins
Aim

    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 overview of the mathematical and software principles behind 2D and 3D visualisation, the viewing pipeline, and practical implementation in the widely used OpenGL graphics library. Representative GUI based 2D and 3D OpenGL applications using the Windows environment are used. Reference is also made to the programming model employed in OpenGL-ES, the version of OpenGL created for embedded devices and the basis for Android and iPhone apps. Hands-on exercises and an assignment supplement the learning process.

Syllabus
    • Mathematical principles behind 2D and 3D visualisation, Matrix transformations, The viewing pipeline, Modelling, viewing and projection, OpenGL graphics library.
    • Development of CG applications using OpenGL and Windows, OpenGL-ES.
Intended learning outcomes On successful completion of this module a student should be able to:
1. Apply the principles of the viewing pipeline to compute device coordinates from a suitable ‘world coordinate system’ model.
2. Use the mathematical basis behind 2D/3D modelling and viewing to solve visualisation problems in OpenGL.
3. Create simple interactive computer graphics based applications using OpenGL and Windows.
4. Evaluate the major differences between the fixed pipeline approach to visualisation and the model employed in OpenGL-ES.


Management for Technology

Module Leader
  • Stephen Carver
Aim

    The importance of technology leadership in driving the technical aspects of an organisations 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.


Syllabus
    • 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. 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), students 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 a student 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 themselves and others to improve 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 their judgements through constructive communication and negotiating skills.

Small-Scale Parallel Programming

Module Leader
  • Dr Salvatore Filippone
Aim

    The advent of multi-core processors in the commodity desktop computer market has shifted the emphasis from traditional single threaded computing models to more advanced methods in order to take advantage of the additional processing power that is now available. This has implications for both the traditional high performance computing sector and the workstation market. This course aims to explore the different parallel processing techniques now available on small scale computer systems, such as multi-core desktop computers and GPU devices.


Syllabus
    Introduction to Parallel and Multi-Threaded Programming, Safety and Liveness: Synchronisation Techniques, OpenMP – concepts, structures and usage.Using CUDA to solve general purpose problems on the GPU, Software Tools (debugging and optimisation).
Intended learning outcomes On successful completion of this module a student should be able to:
1. Apply a systematic application of the techniques employed in multi-threaded processing, and identification of the most common difficulties associated with parallel programming,
2. Demonstrate an understanding of race conditions and blocking, and application of synchronisation techniques as a method of tackling these difficulties.
3. Demonstrate an ability to implement solutions using CPU and GPU technologies.
4. Use and critically evaluate automated tools for the design of source code and debugging of multi-threaded programs.

High Performance Technical Computing

Module Leader
  • Dr Irene Moulitsas
Aim
    The aim of this module is to teach the student the modern computational skills on a key grid platform. Many interesting scientific problems require analysis of large datasets. For such problems, harnessing distributed computing and storage resources is clearly of great value. Furthermore, the natural parallelism inherent in many data analysis procedures makes it feasible to use distributed resources efficiently.


Syllabus

    • The focus of this module is on parallel algorithms and domain decomposition techniques which are suitable for simulation on High Performance Distributed Computing systems. Emphasis is on algorithms for execution on loosely coupled distributed systems, like grid-systems.
    • Data-intensive computing algorithms like distributed data mining and data warehousing.
    • Parallel numerical algorithms to solve model applications will be discussed and studied through implementation in the hands-on part of the course.
    • Load-balancing methods and domain decomposition techniques will be introduced.


Intended learning outcomes On successful completion of this module a student should be able to:
1. Demonstrate knowledge and a critical awareness of the need to carry out scientific computing on the grid platforms.
2. Understand elements of parallel program design.
3. Understand the challenges and limitations of the parallelisation process including scalability (Amdahl and Gustafson laws) and load-balancing.
4. Apply knowledge of intensive computational parallel/distributed techniques to solve a practical problem in scientific computing on the grid platforms (including some awareness of debugging methods).
5. Employ techniques to validate, verify and evaluate the performance and efficiency of parallel programs.



Requirements Analysis and System Design

Module Leader
  • Dr Salvatore Filippone
Aim

    This course aims to provide a more in-depth look at the software life-cycle phases, requirements engineering and design of applications.


Syllabus
    • Software Development Life Cycles
    • Requirements Analysis (user requirements, systems requirement specification, functional & non-functional requirement, software requirements specification, modelling and prototyping, structured analysis, formal specification)
    • System modelling: UML diagrams, behavioural models, structural models, introduction to model checking and formal specifications
    • Design & Implementation: design fundamentals, design architecture, architectural styles, design patterns, data design, objected oriented design, distributed systems design, component based design, data flow oriented design, data oriented design, real time design
Intended learning outcomes On successful completion of this module a student should be able to:
1. Distinguish between the different software development lifecycle models and evaluate which would be the most relevant in a particular situation;
2. Demonstrate conceptual knowledge of requirements planning with respect to the software engineering process;
3. Prepare the relevant requirement documents for each stage of the software project, having performed the required analysis;
4. Propose and implement requirements models for a specified problem;
5. Differentiate the range of software development design techniques in common use and construct the most suitable software designs according to specific functional and non-functional requirements.

Cloud Computing

Module Leader
  • Dr Salvatore Filippone
Aim

    The aim of this module is to provide students with the necessary knowledge and understanding of virtualisation technologies and their application to the provision of on-demand computational resources, as well as a wider understanding of how those resources are consumed through Cloud Computing services.



Syllabus
    • Virtualisation
    • Related Internet technologies (tbc)
    • Introduction to Cloud Computing
    • Topics in Cloud Computing
    • Cloud Environments and Technologies
    • Applications of Cloud Computing

Intended learning outcomes On successful completion of this module a student should be able to:
1. Demonstrate understanding and knowledge of key virtualisation technologies, and their application to Cloud Computing infrastructure;
2. Identify the characteristics of the Cloud Computing platform and understand how these differ from existing distributed computing environments;
3. Critically assess the characteristics of Cloud Computing technologies, and understand how they affect the implementation of Cloud based software;
4. Identify the non-technical challenges that affect the implementation and use of Cloud enabled software;
5. Compare and contrast the suitability of different Cloud Computing approaches to different types of computational problem;
6. Develop and implement Cloud enabled software to solve a specified computational problem.


Software Testing and Quality Assurance

Module Leader
Aim

    This course aims to address issues concerned with related to the quality of software, validation and verification, and software standards.



Syllabus
    • Verification & Validation (verification and validation planning, software testing techniques & strategies, preparing test cases and test environments, unit testing and mocks/fakes/stubs, integration testing, validation testing, system testing, regression testing, customer acceptance testing, advanced debugging, automated static analysis, test documentation, Test Driven Development)
    • Test Management.
    • Software Quality (Introduction to Software Quality, Quality Management (Assurance, Planning and Control), Product quality and process quality, Quality Metrics and Standards, Process Improvement, Reliability).
    • Evolution & Software Maintenance (version & change control, maintainability & maintenance, re-engineering, refactoring, reverse engineering).
    • Software Engineering Standards (ISO, IEEE).
Intended learning outcomes On successful completion of this module a student should be able to:
1. Design and implement software testing strategies, including documentation of testing requirements and outcomes at each stage of the software design and implementation process;
2. Appraise the importance of software testing within the context of the software development lifecycle;
3. Evaluate the relationship between software testing and software quality;
4. Assess the chief factors influencing the evolution of software, including the need for version control, documentation and planned maintenance tasks;
5. Identify the key standards relevant to software quality and assess their impact on each phase of the development lifecycle.

Advanced Java

Module Leader
  • Dr Irene Moulitsas
Aim

    The Java language has become an essential tool for developers of web-based, network centric and mobile device based applications. This module aims to provide the student with the necessary skills to develop robust software using the Java language. The principle elements of the language, associated class libraries and good design principles are covered. Comparisons are made along the way with C++. Hands-on programming exercises using a leading development environment and culminating in the construction of a fully functional three-tier application forms an important part of the course.


Syllabus
    Elements of the Java Standard Edition, Basic and advanced language constructs, Comparisons with C++, Java libraries for I/O, Collections and GUI development, Design principles and patterns ,The Netbeans and development environment, Documentation tools.
Intended learning outcomes On successful completion of this module a student should be able to:
1. Demonstrate knowledge and skills in developing advanced object oriented software using Java.
2. Demonstrate an appreciation and practical knowledge of the advanced tools available for Java software development.
3. Critically evaluate the Java language and associated libraries for the development of software applications.

Applications in Practical High-End Computing - Group Project

Module Leader
  • Dr Irene Moulitsas
Aim

    This module aims to provide the student with skills in the areas of: the software quality and project management, technical/engineering applications and cluster computing so that they can undertake a group project.

Syllabus
    • Project Management (risk analysis, estimation models, project planning and scope definition, communication and team working)
    • Software Metrics & Quality Assurance (definition, collection, quality metrics, productivity metrics, the review process, software reliability, using software quality metrics)
    • Automation Using Software Tools (overview of CASE, project management tools, documentation tools, quality assurance tools, analysis and design tools, integration and testing tools, maintenance tools)
    • Methods for coding and validating technical and engineering applications –f round-off and ill-conditioning
    • Algorithmic stability and performance
    • Specification and performance of computing clusters
    • Validation and tuning of applications on medium-scale distributed architectures.
Intended learning outcomes

On completion of this module the student will be able to:

  • Demonstrate a systematic understanding of the key management tasks involved in implementing a software project in terms of technical requirements, planning and estimation
  • Identify and implement the key techniques used in maintaining a software project, such as identification of critical project metrics, comprehensive quality management and risk assessment
  • Show proficiency in the use of a number of automated tools used to assist the software engineering process, such as project design, documentation and code analysis
  • Show high-level of competence in the use and management of cluster computing for technical/engineering/scientific applications
  • Work as part of a team using coordination, negotiation and interfacing skills.

Fees and funding

European Union students applying for university places in the 2017 to 2018 academic year and the 2018 to 2019 academic year will still have access to student funding support. Please see the UK Government’s announcement (21 April 2017).

Cranfield University welcomes applications from students from all over the world for our postgraduate programmes. The Home/EU student fees listed continue to apply to EU students.

MSc Full-time £10,000
MSc Part-time £10,000 *
  • * Fees can be paid in full up front, or in equal annual instalments, up to a maximum of two payments per year; first payment on or before registration and the second payment six months after the course start date. Students who complete their course before the initial end date will be invoiced the outstanding fee balance and must pay in full prior to graduation.

Fee notes:

  • The fees outlined apply to all students whose initial date of registration falls on or between 1 August 2018 and 31 July 2019.
  • All students pay the tuition fee set by the University for the full duration of their registration period agreed at their initial registration.
  • A non-refundable deposit is payable on offer acceptances and will be deducted from your overall tuition fee.  Home/EU Students will pay a £500 deposit.  Overseas Students will pay a £1,000 deposit.
  • Additional fees for extensions to the agreed registration period may be charged and can be found below.
  • Fee eligibility at the Home/EU rate is determined with reference to UK Government regulations. As a guiding principle, EU nationals (including UK) who are ordinarily resident in the EU pay Home/EU tuition fees, all other students (including those from the Channel Islands and Isle of Man) pay Overseas fees.

For further information regarding tuition fees, please refer to our fee notes.



MSc Full-time £20,000
MSc Part-time £20,000 *
  • * Fees can be paid in full up front, or in equal annual instalments, up to a maximum of two payments per year; first payment on or before registration and the second payment six months after the course start date. Students who complete their course before the initial end date will be invoiced the outstanding fee balance and must pay in full prior to graduation.

Fee notes:

  • The fees outlined apply to all students whose initial date of registration falls on or between 1 August 2018 and 31 July 2019.
  • All students pay the tuition fee set by the University for the full duration of their registration period agreed at their initial registration.
  • A non-refundable deposit is payable on offer acceptances and will be deducted from your overall tuition fee.  Home/EU Students will pay a £500 deposit.  Overseas Students will pay a £1,000 deposit.
  • Additional fees for extensions to the agreed registration period may be charged and can be found below.
  • Fee eligibility at the Home/EU rate is determined with reference to UK Government regulations. As a guiding principle, EU nationals (including UK) who are ordinarily resident in the EU pay Home/EU tuition fees, all other students (including those from the Channel Islands and Isle of Man) pay Overseas fees.

For further information regarding tuition fees, please refer to our fee notes.



Funding Opportunities

To help students find and secure appropriate funding, we have created a funding finder where you can search for suitable sources of funding by filtering the results to suit your needs. Visit the funding finder.

Postgraduate Loan from Student Finance England
A Postgraduate Loan is now available for UK and EU applicants to help you pay for your Master’s course. You can apply for a loan at GOV.UK

Santander MSc Scholarship
The Santander Scholarship at Cranfield University is worth £5,000 towards tuition fees for full-time master's courses. Check the scholarship page to find out if you are from an eligible Santander Universities programme country.

Chevening Scholarships
Chevening Scholarships are awarded to outstanding emerging leaders to pursue a one-year master’s at Cranfield university. The scholarship includes tuition fees, travel and monthly stipend for Master’s study.

Cranfield Postgraduate Loan Scheme (CPLS)
The Cranfield Postgraduate Loan Scheme (CPLS) is a funding programme providing affordable tuition fee and maintenance loans for full-time UK/EU students studying technology-based MSc courses.

Commonwealth Scholarships for Developing Countries
Students from developing countries who would not otherwise be able to study in the UK can apply for a Commonwealth Scholarship which includes tuition fees, travel and monthly stipend for Master’s study.

Future Finance Student Loans
Future Finance offer student loans of up to £40,000 that can cover living costs and tuition fees for all student at Cranfield University.

Erasmus+ Student Loans
This new loan scheme for EU students is offered by Future Finance and European Investment Fund and provides smart, flexible loans of up to £9,300.

Entry requirements

A first or second class UK Honours degree (or equivalent), in aeronautical, mechanical or electrical engineering or computer science or be applying as part of a recognised double-degree programme with their home EU institution.

Entry level C Programming experience is advisable but not required. Applications from candidates with lesser qualifications but with considerable relevant work experience will be considered.

English Language

If you are an international student you will need to provide evidence that you have achieved a satisfactory test result in an English qualification. Our minimum requirements are as follows:

IELTS Academic – 6.5 overall
TOEFL – 92
Pearson PTE Academic – 65
Cambridge English Scale – 180
Cambridge English: Advanced – C
Cambridge English: Proficiency – C

In addition to these minimum scores you are also expected to achieve a balanced score across all elements of the test. We reserve the right to reject any test score if any one element of the test score is too low.

We can only accept tests taken within two years of your registration date (with the exception of Cambridge English tests which have no expiry date).

Students requiring a Tier 4 (General) visa must ensure they can meet the English language requirements set out by UK Visas and Immigration (UKVI) and we recommend booking a IELTS for UKVI test.

Applicants who do not already meet the English language entry requirement for their chosen Cranfield course can apply to attend one of our Presessional English for Academic Purposes (EAP) courses. We offer Winter/Spring and Summer programmes each year to offer holders.

Your career

The Software Engineering for Technical Computing masters, attracts enquiries from companies all over the world, who wish to recruit high quality software development 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.

Graduates of this course are in demand by financial software developers, mobile application developers, commercial engineering software developers, automotive, telecommunications, medical and other industries and research organisations, have been particularly successful in finding long-term employment. We have had positive feedback from companies in industries as diverse as finance to computer games studios. As such, we enjoy excellent employment statistics, with over 95% of graduates employed within six months.

Some students may go on to register for PhD degrees, many, on the basis of their MSc research project. Thesis topics are most often supplied by individual companies on in-company problems with a view to employment after graduation - an approach that is being actively encouraged by a growing number of industries.

Below is a list consisting of companies that have previously recruited our graduates:

  • FACTSET
  • Ocado
  • SAP
  • HSBC
  • IBM
  • BluAge
  • FDM
  • UBS
  • Mindsnacks
  • Mandara Capital
  • Commerzbank AG
  • Oracle.

Applying

Online application form. UK students are normally expected to attend an interview and financial support is best discussed at this time. Overseas and EU students may be interviewed by telephone.


Apply Now