School of Electronic Engineering and Computer Science

Postgraduates menu

Machine Learning for Visual Data Analytics with Industrial Experience

MSc ( 2 years Thick Sandwich )


Places on this programme are limited. We will give equal consideration to all applications received by 17 June 2018. We will still accept applications received after this date, but may not be able to offer a place if the programme is full.

How can we design smartphones that sense your mood by reading your facial expressions or recognise hand gestures as a way to make a call? How do we develop systems that quickly and reliably analyse medical scans to assist with cancerous tumour diagnosis or improve the safety of self-driving cars with in-vehicle technology able to detect and modify a vehicle’s behaviour in any environment? These are just some of the fascinating questions that you will strive to answer on this programme.

This programme is intended to respond to a growing skills shortage in research and industry for engineers with a high level of training in the analysis and interpretation of images and video. It covers both low-level image processing and high-level interpretation using state-of-the-art machine learning methodologies. In addition, it offers high-level training in programming languages, tools and methods that are necessary for the design and implementation of practical computer vision systems.

You will be taught by world-class researchers in the fields of multimedia analysis, vision-based surveillance, structure from motion and human motion analysis.

This programme will:

  • Give you experience of working on cutting-edge, live research projects, gaining hands-on experience.
  • Provide you with the skills and knowledge that will prepare you for a career either in industry or in further research.
  • Teach you the theoretical knowledge and practical application of methods in Computer Vision and Image Processing.
  • Give you programming skills in Matlab or C/C++.
  • School you in sophisticated data collection and analysis techniques.

Industrial Experience

The industrial placement takes place from the September following the taught part of the MSc and is for a maximum of 12 months.  It is a student's responsibility to secure their own placement, but the EECS Placement Team will provide support. The Placement Team source and promote suitable opportunities, assist with applications, and with interview preparation.

The industrial placement consists of 8-12 months spent working with an appropriate employer in a role that relates directly to your field of study. The placement is currently undertaken after you have completed and passed the taught component of the degree and submitted your MSc project.  The placement will provide you with the opportunity to apply the key technical knowledge and skills that you have learnt in your taught modules, and will enable you to gain a better understanding of your own abilities, aptitudes, attitudes and employment potential. The module is only open to students enrolled on a programme of study with integrated placement.

In the event that you are unable to secure a placement we will transfer you onto the 1 year FT taught programme without the Industrial Experience.  This change will also apply to any student visa you hold at the time.

Why study your MSc in Computer Vision at Queen Mary?

Queen Mary has a prestigious history in computing and electronic engineering, we had one of the first Computer Science Departments in the country, and The School of Electronic Engineering and Computer Science is rated in the top 20 universities in the UK for studying computer science and electronic engineering.

  • We are internationally recognised for our pioneering and ground-breaking research, and innovative public engagement programme
  • Our enthusiasm for our research keeps our teaching exciting and up to date. Nine of our staff hold prestigious awards for teaching
  • We also have excellent links with industry, working together on commercial and research projects.


Our research-led approach

Your tuition will be delivered by field leading academics engaged in world class research projects in collaboration with industry, external institutions and research councils.


Our strong links with industry

  • We have collaborations, partnerships, industrial placement schemes and public engagement programmes with a variety of organisations, including Vodafone, Google, IBM, BT, NASA, BBC and Microsoft
  • Industrial projects scheme  - To support industrial experience development, you can to do your final project in collaboration with an industrial partner.


The School of Electronic Engineering and Computer Science offers taught postgraduate students their own computing laboratory. MSc students have exclusive use of the top floor in our purpose-built, climate controlled, award winning informatics teaching laboratory (ITL) outside of scheduled laboratory sessions. The ITL hosts over 250 state-of-the-art PCs capable of multimedia production and several laser printers. In addition, there are video conference facilities, seminar rooms, and on-site teaching services and technical support. There are also a number of breakout spaces available to students with full wi-fi access allowing you use your own mobile devices.

The ITL is primarily used for taught laboratory sessions and regularly hosts research workshops and drop-in lab facilities. For postgraduate students on taught and research degrees there are specialist laboratories to use for carrying out research. Our augmented human interaction (AHI) laboratory combines pioneering technologies including full-body and multi-person motion capture, virtual and augmented reality systems and advanced aural and visual display technologies. We also have specialist laboratories in multimedia; telecommunication networks; and microwave antennas. In addition to these spaces, PhD students have generous study space in our research laboratories. In 2011 we completed the £2m development of new experimental facilities in Antennas and Media and Arts Technology. We formed the Interdisciplinary Informatics Hub in Collaboration with the Schools of Biological and Chemical Sciences and Mathematical Sciences. These laboratories provided a meeting place for postgraduates from the three Schools to interact and exchange ideas.


Full-time with Industrial Experience Option

Students take four modules in Semester 1 (two core and two optional) and four modules in Semester 2 (two core and two optional).

The modules listed below provide some general guidance on what you may be expected to learn during each semester and year of this degree. The exact modules available may vary depending on staff availability, research interests, new topics of study, timetabling and student demand.

Year 1

Semester 1

  • Machine Learning (15 credits)
  • Introduction to Computer Vision (15 credits)

Plus two options from:

  • Computer Graphics (15 credits)
  • Big Data Processing (15 credits)
  • Data Mining (15 credits)

Semester 2

  • Machine Learning for Visual Data Analytics (15 credits)
  • Deep Learning and Computer Vision (15 credits)

Plus two options from:

  • C++ for Image Processing (15 credits)
  • Digital Media and Social Networks (15 credits)
  • Artificial Intelligence (15 credits)

Semester 3

  • Project (60 credits)
    • Below are examples of past MSc projects:
      • Automatic Road Segmentation
        This project, undertaken by a Yamaha Motors Ltd sponsored student, aimed at the identification of the location of the road on images taken from a moving vehicle. The project was based on machine learning methodologies, more specifically decision forests, for the classification of each local area according to features such as colour and motion. The developed method was tested on publicly available datasets on which it achieved state of the art results.
      • 3D face recostruction from a few images
        This project, aimed at the 3D reconstruction of a human face from a few images taken from depth-RGB cameras (such as Kinect cameras). It builds on general methodologies for reconstruction of general, rigid 3D objects and improves them by using information about the appearance and structure of the face. The results of face reconstruction can have applications in security (eg, for face recognition) or for face animation.

Year 2

  • MSc Industrial Placement Project




Further information

We aim to deliver your programme so that it closely matches the way in which it has been described to you by QMUL in print, online, and/or in person. Please be assured that we review our modules on a regular basis, in order to continue to offer innovative and exciting programmes.

Visit the website:


Postgraduate Administrator
School of Electronic Engineering and Computer Science
Tel: +44 (0)20 7882 7333

Entry requirements

Your skills and knowledge will be valuable in all industries that require intelligent processing and interpretation of image and video. This includes industries in directly related fields, such as multimedia indexing and retrieval (eg, Google, Microsoft), motion capture (eg, Vicon), media production (eg, Sony, Technicolor, Disney), medical imaging, security and defence (eg, Qinetiq), robotics, and industries in related areas that require good knowledge of machine learning, signal processing and programming.

A number of our academics have common research projects with industrial partners such as Disney, BBC, Technicolor and ST Microelectronics, and take on consultancy work with industry.

Our staff draws on this industry experience to inform and enrich their teaching, bringing theoretical subjects to life. In addition, several of the final year projects are offered in collaboration with research institutes or industrial partners (

You will also be ideally placed to pursue further research, including continuing onto PhD studies. We will award two PhD fee waivers for top ranked students in this MSc who desire to continue into our PhD programme.

International applicants

Students from outside of the UK help form a global community here at Queen Mary. For detailed country specific entry requirements please visit the International section of our website. If your first language is not English, you must provide evidence of your English language proficiency. You can find details on our English language entry requirements here:

If you do not meet language or scholarly requirements it might be possible for you to undertake foundation or pre-sessional programmes that will prepare you for the masters programme. For more information, please contact the Admissions Office.

If you are unable to find the information you require, please contact the Admissions Office for assistance.

The Admissions Office can be contacted here:

International applicants

Students from outside of the UK help form a global community here at Queen Mary. For detailed country specific entry requirements please visit the International section of our website. If your first language is not English, you must provide evidence of your English language proficiency. You can find details on our English language entry requirements here:

If you do not meet language or scholarly requirements it might be possible for you to undertake foundation or pre-sessional programmes that will prepare you for the masters programme. For more information, please contact the Admissions Office.

If you are unable to find the information you require, please contact the Admissions Office for assistance.

The Admissions Office can be contacted here:

Learning and teaching

As a student at Queen Mary, you will play an active part in your acquisition of skills and knowledge. Teaching is by a mixture of formal lectures and small group seminars. The seminars are designed to generate informed discussion around set topics, and may involve student presentations, group exercise and role-play as well as open discussion. We take pride in the close and friendly working relationship we have with our students. You are assigned an Academic Adviser who will guide you in both academic and pastoral matters throughout your time at Queen Mary.

All modules are taught through a combination of lectures and practical lab work. You can expect two to three hours of contact time per module, per week.

Independent study

For every hour spent in classes you will be expected to complete further hours of independent study. Your individual study time could be spent preparing for, or following up on formal study sessions; reading; producing written work; completing projects; and revising for examinations.

The direction of your individual study will be guided by the formal study sessions you attend, along with your reading lists and assignments. However, we expect you to demonstrate an active role in your own learning by reading widely and expanding your own knowledge, understanding and critical ability.

Independent study will foster in you the ability to identify your own learning needs and determine which areas you need to focus on to become proficient in your subject area. This is an important transferable skill and will help to prepare you for the transition to working life.


All modules are examined through a combination of coursework and written examinations taken in May/June. To obtain an MSc, you must gain passes in six of the eight modules taken with an overall average of 50 per cent. In addition to the above, the MSc requires that a satisfactory individual project be completed. If you do not pass the written examinations you will only be allowed to attempt the project after passing resit examinations the following May.


You will also be assessed on a supervised 10,000-15,000-word dissertation.


Tuition fees for Home and EU students

2018/19 Academic Year
Thick Sandwich £9,250

Tuition fees for International students

2018/19 Academic Year
Thick Sandwich £19,500


There are a number of sources of funding available for Masters students.

These include a significant package of competitive Queen Mary University of London (QMUL) bursaries and scholarships in a range of subject areas, as well as external sources of funding.

Queen Mary bursaries and scholarships

We offer a range of bursaries and scholarships for Masters students including competitive scholarships, bursaries and awards, some of which are for applicants studying specific subjects.

Find out more about QMUL bursaries and scholarships.

Alternative sources of funding

Home/EU students can apply for a range of other funding, such as Professional and Career Development Loans, and Employer Sponsorship, depending on their circumstances and the specific programme of study.

Overseas students may be eligible to apply for a range of external scholarships and we also provide information about relevant funding providers in your home country on our country web pages.

Download our Postgraduate Funding Guide [PDF] for detailed information about postgraduate funding options for Home/EU students.

Read more about alternative sources of funding for Home/EU students and for Overseas students.

Tel: +44 (0)20 7882 5079

Other financial help on offer at Queen Mary

We offer one to one specialist support on all financial and welfare issues through our Advice and Counselling Service, which you can access as soon as you have applied for a place at Queen Mary.

Our Advice and Counselling Service also has lots of Student Advice Guides on all aspects of finance including:

Tel: +44 (0)20 7882 8717

Graduate employment

Queen Mary's Computer Science postgraduates go on to work in a wide variety of careers, mostly within IT and information services.

The broad range of skills gained through programmes in this School, coupled with multiple opportunities for extra-curricular activities and work experience, has enabled postgraduates to move into careers such as:

  • Technical Analyst, Credit Suisse
  • Interactive Systems Developer, Sky
  • Software Developer, Accenture
  • Analyst Technical Associate, Bank of America Merrill Lynch
  • IT Contractor, FDM
  • Computer Analyst, ITRS Group
  • IT Developer, Qube Global Software
  • Team Manager, Bromley-by-Bow Centre
  • Computer Programmer, Rightmove
  • Computer Consultant, Mac Experts Ltd
  • Graduate Engineer, Ministry of Defence

Throughout the course, postgraduates have access to a careers programme to prepare them for applying for work after graduation. This programme includes workshops on job hunting and job applications as well as employer events to facilitate networks and help students to explore their options.

Recent careers events open to Computer Science postgraduates include the IT and Technology Fair, featuring Accenture, Babcock, BskyB, FactSet, Framestore, IBM, one-to-one sessions with Morgan Stanley, IBM and Accenture, IT company presentations, and Start Up Stand Up for those interested in working with technology start ups and SMEs.

Queen Mary’s location between Canary Wharf, the City and the Olympic Village redevelopment means that there are substantial opportunities for on campus and local part time work and work experience. On campus there are 1200 job and volunteer opportunities ranging from E-learning Assistant to Website Administrator and from Society President to Student Mentor. QTemps job agency offers work suitable for current students and recent graduates, QMSU Volunteering facilitates volunteering and QM JobOnline hosts over 800 part time and full time job vacancies.

Read more about our careers programmes and range of work experience opportunities on the Queen Mary Careers pages.



Return to top