Medical imaging is a rapidly-growing discipline within the healthcare sector, involving clinicians, physicists, computer scientists and those in IT industries.
This programme delivers the expertise you'll need to forge a career in medical imaging, including radiation physics, image processing, biology, computer vision, pattern recognition, artificial intelligence and machine learning.
This programme is studied full-time over 12 months and part-time over 48 months. It consists of eight taught modules and an extended project.
Example module listing
The following modules are indicative, reflecting the information available at the time of publication. Please note that not all modules described are compulsory and may be subject to teaching availability and/or student demand.
To support your learning, we hold regular MSc group meetings where any aspect of the programme, technical or non-technical, can be discussed in an informal atmosphere. This allows you to raise any problems that you would like to have addressed and encourages peer-based learning and general group discussion.
We provide computing support with any specialised software required during the programme, for example, Matlab.
The Department’s student common room is also covered by the university’s open-access wireless network, which makes it a very popular location for individual and group work using laptops and mobile devices. There is also a Faculty quiet room for individual study.
We pride ourselves on the many opportunities that we provide to visit collaborating hospitals. These enable you to see first-hand demonstrations of medical imaging facilities and to benefit from lectures by professional practitioners.
To support material presented during the programme, you will also undertake a selection of ultrasound and radiation detection experiments, hosted by our sister MSc programme in Medical Physics.
The taught postgraduate Degree Programmes of the Department are intended both to assist with professional career development within the relevant industry and, for a small number of students, to serve as a precursor to academic research.
Our philosophy is to integrate the acquisition of core engineering and scientific knowledge with the development of key practical skills (where relevant).
To fulfil these objectives, the programme aims to:
Medical Imaging is a rapidly growing discipline within the healthcare sector, incorporating engineers, physicists, computer scientists and clinicians. It is driven by the recent rapid development of 3-D Medical Imaging Systems, fuelled by an exponential rise in computing power.
New methods have been developed for the acquisition, reconstruction, processing and display of digital medical-image data with unprecedented speed, resolution and contrast.
This programme in Medical Imaging is aimed at training graduates for careers in this exciting multi-disciplinary area, and our graduates can expect to find employment in the medical imaging industry or the public health care sector.
It represents a blend of fundamental medical physics topics concerned with image acquisition and reconstruction coupled with imaging science and image engineering topics such that graduates understand how images are formed and how advanced machine-based methods can be bought to bare to provide new diagnostic information.
We often give our students the opportunity to acquire international experience during their degrees by taking advantage of our exchange agreements with overseas universities.
In addition to the hugely enjoyable and satisfying experience, time spent abroad adds a distinctive element to your CV.
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
This intensive programme offers an exciting opportunity to learn from world leaders in both informatics and linguistics. Drawing from our cutting-edge research, the programme’s content covers all areas of speech and language processing, from phonetics, speech synthesis and speech recognition to natural language generation and machine translation.
This flexible programme provides research or vocational training and can be either freestanding or lead to PhD study. The modular nature of the programme allows you to tailor it to your own interests.
Taught by leading researchers from Linguistics & English Language, the Centre for Speech Technology Research and the School of Informatics, this programme combines elements of linguistics, computer science, engineering and psychology.
You will develop up-to-date knowledge of a broad range of areas in speech and language processing and gain the technical expertise and hands-on skills required to carry out research and development in this challenging interdisciplinary area.
You study two semesters of taught courses, followed by a dissertation.
Most core compulsory courses have both computational and mathematical content. A few optional courses need a stronger mathematical background. Courses in the second semester can be tailored to your own interests and abilities.
Option courses may include:
This programme aims to equip you with the technical knowledge and practical skills required to carry out research and development in the challenging interdisciplinary arena of speech and language technology.
You will learn about state-of-the-art techniques in speech synthesis, speech recognition, natural language processing, dialogue, language generation and machine translation.
You will also learn the theory behind such technologies and gain the practical experience of working with and developing real systems based on these technologies. This programme is ideal preparation for a PhD or working in industry.
This programme will provide you with the specialised skills you need to perform research or develop technology in speech and language processing. It will also serve as a solid basis for doctoral study.
The theoretical application of mathematics to the world of finance allows you to make good, informed decisions in the face of uncertainty. With the growth and progression of business across the globe, the need for those who can understand quantitative financial methods are becoming increasingly lucrative, sought-after individuals. For those with a strong mathematical background, and a wish to pursue a finance career, this programme is the ideal introduction to this exciting and expanding field.To understand, apply and develop these sophisticated methods requires a good understanding of both advanced mathematics and advanced financial theory. By combining the financial expertise in the University of Exeter Business School with our internationally respected Mathematics department, this comprehensive MSc programme will prepare you for careers in areas that require expert skills in mathematical and financial modelling, computational analysis and business management.
You will gain essential, complementary skills in multiple areas of study such as probability and stochastic analysis, option pricing, risk analysis and extremes, computational methods using MATLAB/C++, financial management and investment analysis. In addition, you will branch into a specialist area of study as you conduct a substantial project in a field of your choosing. The project will allow you to develop your research, computational and modelling skills with support from staff who have extensive experience working in multiple financial services and insurance industries.
The programme prepares you for a career in financial modelling within financial institutions themselves and within other sectors. It builds upon the success of Exeter’s well-established range of Masters programmes in Finance and related areas, many of whose graduates now hold senior positions in areas such as corporate financial strategy, financial planning, treasury and risk management and international portfolio management.
With the strong links between the College and the Met Office, the course also prepares you for career opportunities within reinsurance and credit risk management, especially in the development of financial models that rely on weather/climate systems.
The taught element of the programme takes place between October and May and is arranged into two 12-week teaching semesters.
Recent examples of compulsory modules are as follows; Methods for Stochastics and Finance; Analysis and Computation for Finance; Mathematical Theory of Option Pricing; Fundamentals of Financial Management; Research Methodology; Advanced Mathematics Project.
Some recent examples are as follows; Topics in Financial Economics; Investment Analysis 1; Banking and Financial Services; Derivatives Pricing; Domestic and International Portfolio Management; Investment Analysis II; Financial Modelling; Advanced Corporate Finance; Alternative Investments; Quantitative and Research Techniques; Advanced Econometrics; Dynamical Systems and Chaos; Pattern Recognition; Introduction to C++; Level 3 Mathematics Modules.
The Intelligent Systems MSc degree course is designed to give graduates the understanding, practical knowledge and expertise to evaluate, design and build intelligent systems using an extensive range of tools and techniques.
The Intelligent Systems MSc will prepare you for work developing intelligent control and engineering systems. You will study Artificial Intelligence, Agents and Multi-agent Systems, Pattern Recognition, Computer Vision and Biologically Inspired Methods. There are also opportunities to explore a broad range of optional modules allowing you the freedom to develop your study pathway to reflect your interests.
You will complete the course in one year, studying September to September and taking a combination of required and optional modules totalling 180 credits, including 60 credits that will come from an individual project of 15,000 words.
For graduates in engineering, computing or a related scientific discipline, with a good knowledge of computer programming and mathematics, from this programme you will gain specialist training in designing, building and evaluating intelligent systems using a range of tools and techniques in preparation for a career in research or industry.
We use lectures, seminars and group tutorials to deliver most of the modules on the programme. You will also be expected to undertake a significant amount of independent study.
The primary method of assessment for this course is a combination of written examinations, essays, coursework and individual or group projects and oral presentations. The research project will be assessed through a dissertation.
Our graduates have gone on to pursue successful careers in industry, commerce and academia.
This MSc is taught at the UK’s longest established centre for artificial intelligence, which remains one of the best in the world.
Our research draws on neuroscience, cognitive science, linguistics, computer science, mathematics, statistics and psychology to span knowledge representation and reasoning, the study of brain processes and artificial learning systems, computer vision, mobile and assembly robotics, music perception and visualisation.
We aim to give you practical knowledge in the design and construction of intelligent systems so you can apply your skills in a variety of career settings.
You follow two taught semesters of lectures, tutorials, project work and written assignments, after which you will learn research methods before individual supervision for your project and dissertation.
You will choose a 'specialist area' within the programme, which will determine the choice of your optional courses:
You can choose from a variety of optional courses including:
Our students are well prepared for both employment and academic research. The emphasis is on practical techniques for the design and construction of intelligent systems, preparing graduates to work in a variety of specialisms, from fraud detection software to spacecraft control.