Medical engineering combines the design and problem-solving skills of engineering with medical and biological sciences to contribute to medical device solutions and interventions for a range of diseases and trauma.
This exciting and challenging programme will give you a broad knowledge base in this rapidly expanding field, as well as allowing you to specialise through your choice of optional modules.
We emphasise the multidisciplinary nature of medical engineering and the current shift towards the interface between engineering and the life sciences. You could focus on tissue engineering, biomaterials or joint replacement technology among a host of other topics.
Whether you’re an engineer or surgeon, or you work in sales, marketing or regulation, you’ll gain the knowledge and skills to launch or develop your career in this demanding sector.
Institute of Medical and Biological Engineering
You’ll learn in an exciting research environment where breakthroughs are being made in your discipline. This programme is closely linked to our Institute of Medical and Biological Engineering (IMBE), which focuses on research and education in the fields of medical devices and regenerative medicine. It focuses on innovating and translating new therapies into practical clinical applications.
Our world-class facilities in materials screening analysis, joint simulation, surface analysis, heart valve simulation and tensile and fatigue testing allow us to push the boundaries in medical engineering.
One core module in Semester 1 will give you a background in experimental design and analysis within medical engineering. You’ll look at computational and biological methodologies alongside statistical data analysis and different data visualisation techniques to lay the foundations of your studies.
Optional modules in each semester will allow you to build on this knowledge and focus on specialist topics that suit your own interests and career intentions. You could focus on biomechatronics and medical robotics, spinal biomechanics, surface engineering or computational fluid dynamics analysis and a range of other topics. Depending on your academic or professional background, you may decide to take introductory modules such as Basic Orthopaedic Engineering or Structure and Function of the Body to fill the gaps in your knowledge.
Throughout the programme you’ll complete your Professional Project – an independent piece of research on a topic within mechanical engineering that allows you to demonstrate your knowledge and skills. In the two taught semesters you’ll review the literature around your topic and plan the project, before completing the design, analysis, computation, experimentation and writing up in the summer months.
If you choose to study part-time, you’ll extend your studies over a longer period so you can take fewer modules in each year.
Want to find out more about your modules?
Take a look at the Medical Engineering module descriptions for more detail on what you will study.
Our groundbreaking research feeds directly into teaching, and you’ll have regular interactions with staff who are at the forefront of their disciplines. You’ll have regular contact with them through lectures, seminars, tutorials, small group work and project meetings. Some modules make use of online learning methods or a short course format.
Independent study is also important to the programme, as you develop your problem-solving and research skills as well as your subject knowledge.
You’ll be assessed using a range of techniques including case studies, technical reports, presentations, in-class tests, assignments and exams. Optional modules may also use alternative assessment methods.
The professional project is one of the most satisfying elements of this course. It allows you to apply what you’ve learned to a piece of research focusing on a real-world problem, and it can be used to explore and develop your specific interests.
Recent projects for MSc Medical Engineering students have included:
Career destinations are diverse and include medical engineering within industrial or public sector organisations, regulatory affairs and sales and marketing.
Graduates from this programme have gone on to work in a range of roles for employers such as the clinical research centres, continued in a career in clinical orthopaedics, progressed to a PhD programme.
You’ll also be well prepared to continue with engineering research, whether in industry or at PhD level.
You’ll have access to the wide range of engineering and computing careers resources held by our Employability team in our dedicated Employability Suite. You’ll have the chance to attend industry presentations book appointments with qualified careers consultants and take part in employability workshops. Our annual Engineering and Computing Careers Fairs provide further opportunities to explore your career options with some of the UK's leading employers.
The University's Careers Centre also provide a range of help and advice to help you plan your career and make well-informed decisions along the way, even after you graduate. Find out more at the Careers website
If you are interested in medical imaging and highly sophisticated ways of assisting in diagnostics visually the medical imaging programme comes from a long heritage of major world innovation which was led by research at Aberdeen. Did you know researchers at Aberdeen invented the first MRI scanner (Magnetic Resonance Imaging) for instance? Since this time much has been done to further work on the MRI scanner and deliver some of the most advanced forms of body visualisation tools available to the health area. If you have ever wondered how X rays work or you are interested in the latest radiotherapy techniques to provide therapeutic tools from radiographic equipment and advances this programme not only gives you the theory and practice in applying imaging in a health setting, it also gives you opportunities to think about the technologies involved and the applications. There is a lot of Physics and Maths required behind the different technologies involved in medical imaging so if you have these subjects and a life science background plus engineering or similar science disciplines this will make the programme more accessible.
By the end of the MSc programme you will have received a thorough academic grounding in Medical Imaging, been exposed to the practice of Medical Imaging in a hospital Department, and carried out a short research project. The MSc programme is accredited by the Institute of Physics & Engineering in Medicine as fulfilling part of the training requirements for those wishing to work in the NHS. There are wide ranging career possibilities after graduation. You may wish to go straight into clinic settings to apply your skills within diagnostics or you may wish to study further for a PhD towards teaching or researching. There have also been spin out companies as a result of understanding and applying imaging technologies towards innovative applications. This subject also aligns with some major innovations in Photonics and other areas of medical science which you may like to explore further if you are interested in invention and innovation at the Scottish Innovation Centres: http://www.innovationcentres.scot/
Radiation in Imaging
Introduction to Computing and Image Processing
Biomedical and Professional Topics in Healthcare Science
Imaging in Medicine
Nuclear Medicine and Positron Emission Tomography
Magnetic Resonance Imaging
Medical Image Processing and Analysis
Diagnostic and Radiation Protection
MSc Project for Programme in Medical Physics and Medical Imaging
Find out more detail by visiting the programme web page:
Find out about fees:
*Please be advised that some programmes have different tuition fees from those listed above and that some programmes also have additional costs.
View all funding options on our funding database via the programme page
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Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Data Science at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017).
MSc in Data Science aims to equip students with a solid grounding in data science concepts and technologies for extracting information and constructing knowledge from data. Students of the MSc Data Science will study the computational principles, methods, and systems for a variety of real world applications that require mathematical foundations, programming skills, critical thinking, and ingenuity. Development of research skills will be an essential element of the Data Science programme so that students can bring a critical perspective to current data science discipline and apply this to future developments in a rapidly changing technological environment.
The MSc Data Science programme focuses on three core technical themes: data mining, machine learning, and visualisation. Data mining is fundamental to data science and the students will learn how to mine both structured data and unstructured data. Students will gain practical data mining experience and will gain a systematic understanding of the fundamental concepts of analysing complex and heterogeneous data. They will be able to manipulate large heterogeneous datasets, from storage to processing, be able to extract information from large datasets, gain experience of data mining algorithms and techniques, and be able to apply them in real world applications. Machine learning has proven to be an effective and exciting technology for data and it is of high value when it comes to employment. Students of the Data Science programme will learn the fundamentals of both conventional and state-of-the-art machine learning techniques, be able to apply the methods and techniques to synthesise solutions using machine learning, and will have the necessary practical skills to apply their understanding to big data problems. We will train students to explore a variety visualisation concepts and techniques for data analysis. Students will be able to apply important concepts in data visualisation, information visualisation, and visual analytics to support data process and knowledge discovery. The students of the Data Science programme also learn important mathematical concepts and methods required by a data scientist. A specifically designed module that is accessible to students with different background will cover the basics of algebra, optimisation techniques, statistics, and so on. More advanced mathematical concepts are integrated in individual modules where necessary.
The MSc Data Science programme delivers the practical components using a number of programming languages and software packages, such as Hadoop, Python, Matlab, C++, OpenGL, OpenCV, and Spark. Students will also be exposed to a range of closely related subject areas, including pattern recognition, high performance computing, GPU processing, computer vision, human computer interaction, and software validation and verification. The delivery of both core and optional modules leverage on the research strength and capacity in the department. The modules are delivered by lecturers who are actively engaged in world leading researches in this field. Students of the Data Science programme will benefit from state-of-the-art materials and contents, and will work on individual degree projects that can be research-led or application driven.
Modules for the MSc Data Science programme include:
- Visual Analytics
- Data Science Research Methods and Seminars
- Big Data and Data Mining
- Big Data and Machine Learning
- Mathematical Skills for Data Scientists
- Data Visualization
- Human Computer Interaction
- High Performance Computing in C/C++
- Graphics Processor Programming
- Computer Vision and Pattern Recognition
- Modelling and Verification Techniques
- Operating Systems and Architectures
The Department of Computer Science is well equipped for teaching, and is continually upgrading its laboratories to ensure equipment is up-to-date – equipment is never more than three years old, and rarely more than two. Currently, our Computer Science students use three fully networked laboratories: one, running Windows; another running Linux; and a project laboratory, containing specialised equipment. These laboratories support a wide range of software, including the programming languages Java, C# and the .net framework, C, C++, Haskell and Prolog among many; integrated programme development environments such as Visual Studio and Netbeans; the widely-used Microsoft Office package; web access tools; and many special purpose software tools including graphical rendering and image manipulation tools; expert system production tools; concurrent system modelling tools; World Wide Web authoring tools; and databases.
As part of the expansion of the Department of Computer Science, we are building the Computational Foundry on our Bay Campus for computer science and mathematical science.
- Data Analyst
- Data mining Developer
- Machine Learning Developer
- Visual Analytics Developer
- Visualisation Developer
- Visual Computing Software Developer
- Database Developer
- Data Science Researcher
- Computer Vision Developer
- Medical Computing Developer
- Informatics Developer
- Software Engineer
Have you ever wanted to ‘Mung’ data? Apply Machine Learning techniques? Search for hidden patterns? Be part of Big Data?
This course is your opportunity to specialize as a Data Scientist, one of the most in demand roles across all sectors including health, retail, and energy. Companies such as Google and Microsoft, and also public organisations such as the NHS are struggling to fill their vacancies in this field due to a lack of suitably qualified people. This course is unique in the UK in that it has been developed as a MSc conversion course – if you have a good honours degree in any discipline with a demonstrable mathematical aptitude, an enquiring mind, a practical and analytical approach to problem solving, and an ambition for a career in data science; then this course is for you.
During your time with us, you will develop an awareness of the latest developments in the fields of Data Science and Big Data including advanced databases, data mining and big data tools such as Hadoop. You will also gain substantial knowledge and skills with the SAS business intelligence software suite due to the partnership of the University with the SAS Student Academy.
"We are especially pleased to endorse the new MSc in Data Science. With the explosion of interest and investment in data science teams, our customers cannot get enough graduates with SAS-based analytical skills. Courses such as this new MSc are an important step forward by the University to addressing this skills shortage, especially amongst home students." - SAS
This course covers a very comprehensive range of topics split in to four large modules worth 30 credits each plus the MSc Project worth 60 credits. External speakers from blue-chip and local companies will give seminars to complement your learning, that will be real-world case studies related to the subjects you are studying in your modules. These are designed to improve the breadth of your learning and could lead to ideas that you can develop for your MSc Project.
The course is focused around the underpinning knowledge and practical skills needed for employment within the data sciences industry. There will be 22 hours of lectures; 11 hours of tutorials and 22 hours workshops; 2 hours of examination-based assessment; and 245 hours of independent study, assessed coursework and preparation for examination. This makes a total of 300 hours total learning experience.
A recent report by e-Skills and SAS (Big Data Analytics: An assessment of the demand for labour and skills, 2012-1017) indicates the demand forecast for staff with big data skills is predicted to ”rise by 92% between 2012 and 2017, and by 2017 there will be at least 28,000 job openings for big data staff in the UK each year…”
With this qualification, you’ll be equipped with the skill set and technical knowledge relevant for the data science and big data job market.
The Informatics Research Centre in the School of Computing, Science and Engineering at the University of Salford builds on the history, success and achievements of the research in Computer Science and Information Systems developed at the University of Salford over the last thirty years.
Evolving around Data and Information in all their types and usages, the Centre covers all phases and processes from data pre-processing to engineering and visualisation. The Centre is developing novel methods and systems for the analysis and recognition of various data sets, learning behaviours and causal models. The techniques and systems developed have a wide range of potential applications including digitisation of historical documents, medical diagnosis, semantic tagging, segmentation of types of viewers and their behaviours, text mining and retrieval and data visualisation.
Forensic computing, digital investigation and Cyber security is another area of expertise supported by the centre both at the theoretical and application levels.
Many students go on to further research in the fields of:
Facilities include a new Dell Cloud Computing platform with OpenStack and lab workstations, providing access to software platforms and languages specialized in Machine Learning, Data Mining, Statistical Analysis and Big Data including:
Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Health Data Science at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017).
Healthcare, with an already established strong relationship with Information & Communication Technologies (ICT), is continuously expanding the knowledge forefront as new methods of acquiring data concerning the health of human beings are developed.
Processing this data to extract valuable information about a population (epidemiological applications) or the individual (personalised healthcare applications) is the work of health data scientists. Their work has the potential to improve quality of life on a large scale.
Swansea University is the first institution in the UK to offer this taught master's programme in Health Data Science designed to develop the essential skills and knowledge required of the Health Data Scientist.
- A one year full-time taught master's programme designed to develop the essential skills and knowledge required of the Health Data Scientist.
- The Health Data Science course is also available for three years part-time study.
- An integrated programme of studies tailored to the essential skill set required for Data Scientists operating within healthcare organisations covering key topics in computation, data modeling, visualisation, machine learning and key methodologies in the analysis of linked health data.
- Hands on experiential learning from the professionals behind the Secure Anonymised Information Linkage (SAIL) Databank, a UK-exemplar project for the large scale mining of healthcare data within a secure environment.
- Strong collaboration links with colleagues from the Centre for Health Services Research of the University of Western Australia, a group of leading experts in the analysis of linked health data.
- The Health Data Science course is based within the award winning Centres for Excellence for Administrative Data and eHealth Research of Swansea University, awarded by the Economic and Social Research Council (ESRC) and Medical Research Council (MRC), enhancing the quality of the course.
The Health Data Science course is suitable for those working in healthcare with roles involving the analysis of health data and also computer scientists with experience in working with data from the healthcare domain, as well as biomedical engineers and other similar professions.
Students must complete 6 modules of 20 credits each and produce a 60 credits dissertation on a Health Data Science project. Each module of the programme requires a short period of attendance that is augmented by preparatory and reflective material supplied via the course website before and after attendance.
Health Data Science students are required to attend the University for 1 week (5 consecutive days) for each module in Part One. Attendance during Part Two is negotiated with the supervisor.
Modules on the Health Data Science programme typically include:
Scientific Computing and Health Care
Health Data Modelling
Introductory Analysis of Linked Health Data
Machine Learning in Healthcare
Health Data Visualisation
Advanced Analysis of Linked Health Data
The College of Medicine offers the modules on the Health Data Science course as standalone opportunities for prospective students to undertake continued professional development (CPD) in the area of Health Data Science.
You can enroll on the individual modules for the Health Data Science programme as either an Associate Student (who will be required to complete the module(s) assessments) or as a Non-Associate Student (who can attend all teaching sessions but will not be required to complete any assessments).
For information and advice on applying for any of the continuing education opportunities, please contact the College directly at [email protected].
Postgraduate study has many benefits, including enhanced employability, career progression, intellectual reward and the opportunity to change direction with a conversion course.
From the moment you arrive in Swansea, specialist staff in Careers and Employability will help you plan and prepare for your future. They will help you identify and develop skills that will enable you to make the most of your postgraduate degree and enhance your career options. The services they offer will ensure that you have the best possible chance of success in the job market.
The student experience at Swansea University offers a wide range of opportunities for personal and professional development through involvement in many aspects of student life.
Co-curricular opportunities to develop employability skills include national and international work experience and study abroad programmes and volunteering, together with students' union and athletic union societies, social and leisure activities.
For the MSc Health Data Science course, we are in the process of identifying opportunities for our students to complete volunteering placements with a number of our collaborative partners.