* One-year masters studentships are available for this stream. Each studentship will be worth £5000 and can be taken either as a reduction in fees or as a bursary. Studentships will be awarded based on academic merit and are open to all applicants, regardless of fee status (home/EU/overseas). Please indicate 'Data Science' in the first line of your personal statement.
* Two PhD Studentships targeted at successful graduates from this stream. Two 3-year PhD studentships will be on offer, targeted at students obtaining a minimum of a Pass with Merit on the Data Science stream. These studentships will cover the cost of tuition fees for home/EU applicants and a stipend at standard Research Council rates.
This course is a stream within the broader MRes in Biomedical Research.
The Data Science stream provides an interdisciplinary training in analysis of ‘big data’ from modern high throughput biomolecular studies. This is achieved through a core training in multivariate statistics, chemometrics and machine learning methods, along with research experience in the development and application of these methods to real world biomedical studies. There is an emphasis on handling large-scale data from molecular phenotyping techniques such as metabolic profiling and related genomics approaches. Like the other MRes streams, this course exposes students to the latest developments in the field through two mini-research projects of 20 weeks each, supplemented by lectures, workshops and journal clubs. The stream is based in the Division of Computational and Systems Medicine and benefits from close links with large facilities such as the MRC-NIHR National Phenome Centre, the MRC Clinical Phenotyping Centre and the Centre for Systems Oncology. The Data Science stream is developed in collaboration with Imperial’s Data Science Institute.
Students with a degree in physical sciences, engineering, mathematics computer science (or related area) who wish to apply their numeric skills to solve biomedical problems with big data.
Students will gain experience in analysing and modelling big data from technologically advanced techniques applied to biomedical questions. Individuals who successfully complete the course will have developed the ability to:
• Perform novel computational informatics research and exercise critical scientific thought in the interpretation of results.
• Implement and apply sophisticated statistical and machine learning techniques in the interrogation of large and complex
biomedical data sets.
• Understand the cutting edge technologies used to conduct molecular phenotyping studies on a large scale.
• Interpret and present complex scientific data from multiple sources.
• Mine the scientific literature for relevant information and develop research plans.
• Write a grant application, through the taught grant-writing exercise common to all MRes streams.
• Write and defend research reports through writing, poster presentations and seminars.
• Exercise a range of transferable skills by taking short courses taught through the Graduate School and the core programme of the
MRes Biomedical Research degree.
A wide range of research projects is made available to students twice a year. The projects available to each student are determined by their stream. Students may have access from other streams, but have priority only on projects offered by their own stream. Example projects for Data Science include (but are not limited to):
• Integration of Multi-Platform Metabolic Profiling Data With Application to Subclinical Atherosclerosis Detection
• What Makes a Biological Pathway Useful? Investigating Pathway Robustness
• Bioinformatics for mass spectrometry imaging in augmented systems histology
• Processing of 3D imaging hyperspectral datasets for explorative analysis of tumour heterogeneity
• Fusion of molecular and clinical phenotypes to predict patient mortality
• 4-dimensional visualization of high throughput molecular data for surgical diagnostics
• Modelling short but highly multivariate time series in metabolomics and genomics
• Searching for the needle in the haystack: statistically enhanced pattern detection in high resolution molecular spectra
Visit the MRes in Biomedical Research (Data Science) page on the Imperial College London web site for more details!
The MA Creative Media Arts: Data and Innovation is designed to respond directly to your needs as someone with the ambition to build a career in one of the growth sectors in the UK: the creative and cultural industries. The course delivers a unique combination of media art and design methodologies alongside basic management and business analytics, to help you build a successful career or venture within this dynamic sector. The curriculum has been developed in response to important research findings, demonstrating that growth in the wider economy is being driven by a creative sector founded on a fusion between digital technologies, creative practice and the wider arts and humanities. It's what we call the “fusion hypothesis”. Drawing extensively on this concept we have developed a programme that brings the cultures of art, technology and enterprise into new and generative combinations.
With its emphasis on focused innovation and rapid prototyping the course is unusual in combining a critical media arts perspective with a deep understanding and engagement with the business-led dynamics of the creative industries.
The course is delivered in the context of Bournemouth University’s world renowned Faculty of Media & Communication, known for its contacts at the heart of the media industry. The programme has been developed and lead by leading practitioners from media art contributing business-led research and development insights from the design sector aimed at developing advanced enterprise and creative projects. The image at the top of this page was taken at the Museo Jumex in Mexico City and features work entitled Squidsoup by Liam Birtles, one of the senior lecturers on this course, just one example of the international reach our team has in this field.
Studying this Master’s degree is an ideal next step for applicants from both creative media and the arts and humanities, including areas such as graphic design, visual communications, fine art, performance, audio and sound, and theatre and media production, as well as those from interdisciplinary non-creative backgrounds, such as computer science, geography and engineering, who can demonstrate interest through a creative portfolio or other work experience.
You may have an undergraduate qualification in a related subject or may be able to show your suitability for this programme of study through associated work-experience or evidence of and outputs from other related activities.
Application period/deadline: November 1, 2017 - January 24, 2018
• Research-oriented degree provides an exciting opportunity to study in a leading-edge research environment
• The studies combine both theoretical and practical approach
• Specializations in Applied Computing, Artificial Intelligence, and Computer Egineering
The International Master’s Degree Programme in Computer Science and Engineering (CSE) is a two-year research-oriented programme concentrating on intelligent digital solutions to real world problems. During the past decades, Computer Science and Engineering has had a significant impact into our daily lives. The development continues and soon computers will not be used as separate devices anymore. Instead they will blend into our living environments and offer us rich sets of services through natural and intuitive user interfaces. The graduates from Computer Science and Engineering will play a key role in this development.
The two-year programme has three specialisation options:
• Applied Computing
• Artificial Intelligence
• Computer Engineering
Applied Computing focuses on the next generation of interactive systems that place humans at the focus of the technological development. Adopting a multidisciplinary real-world approach, students have to spend a substantial amount of time working in group projects to develop a variety of systems ranging from interactive online services to games and mobile applications, with a strong focus on innovation and design.
Artificial Intelligence focuses in various fields of AI, such as machine learning, machine vision, and data mining. This specialisation provides students with a solid theoretical understanding and practical skills on processing and analyzing digital data and the ability to create intelligent solutions to real world problems with modern AI techniques.
Computer Engineering focuses on both hardware and software aspects of computing with emphasis on embedded system development. In this specialisation, students also study signal processing and its applications, and work with projects on modern signal processors and embedded computers. The specialisation gives the students a good basis to work with Internet of Things (IoT) applications.
In addition to the core specialization options, students can take optional courses to widen their specialization expertise into:
• Biomedical signal analysis
• Machine learning
• Machine vision
• Signal processing
• Embedded systems
• Ubiquitous computing
This Master’s programme is provided by the Faculty of Information Technology and Electrical Engineering, and students are strongly encouraged to work closely with research groups in the faculty that are international leaders in their fields. The Center for Machine Vision and Signal Analysis (CMVS) is renowned world-wide for its 35 years of expertise in computer vision research. The Center for Ubiquitous Computing (UBICOMP) has created a unique research environment for Ubiquitous Computing including multitouch wall-sized displays, smartphone sensing middleware and sensor networks. Biomimetics and Intelligent Systems Group (BISG) is a fusion of expertise from the fields of computer science and biology. During the studies the research groups provide students trainee and master’s thesis positions, with the possibility to continue as a doctoral student, and even as a post-doctoral researcher.
The programme will provide the graduates with sufficient skills to work in a wide variety of positions offered by research institutes and companies mainly operating in the field of information and communications technology (ICT). The graduates are most likely to be employed in research and development related positions, but also management positions and entrepreneurship fit into the profile.
Possible titles include:
• Research Scientist
• Software Engineer
• System Designer
• Project Manager
Students applying for the programme must possess an applicable B.Sc. degree in computer science, electrical engineering or relevant fields such as physics or applied mathematics.
The Masters in Mechatronics is a fusion of mechanical, electrical, electronic and control engineering. Modern industry depends for its success in global markets on its ability to integrate these subjects into both the manufacturing process and innovative products and systems.
*For suitably qualified candidates.
Modes of delivery of the MSc in Mechatronics include lectures, seminars and tutorials and allow students the opportunity to take part in lab, project and team work.
You will undertake a project where you will apply your newly learned skills and show to future employers that you have been working on cutting-edge projects relevant to the industry.
Career opportunities include manufacturing production systems; system design and manufacture; product engineering and manufacture.
Graduates of this programme have gone on to positions such as:
Senior Software Engineer at Wipro Technologies.
SCAV is designed for engineering or STEM subject graduates. It is particularly suitable for those with a background in electronics, electrical engineering, control systems, or communications who want to play a role in the development of connected and autonomous vehicles, and the Intelligent Transportation Systems Network.
With the advent of smart, connected and autonomous vehicles on the horizon of technical advancements, the automotive industry is facing a developmental challenge. How do we develop a robust technical infrastructure to support the anticipated explosive growth in smart vehicular functions, communications systems and driverless cars? This demands a comprehensive understanding of the technology and a bottom-up approach ensuring robustness and dependability of Electronics, Communications (e.g. V-2-V, V-2-I) and Control Systems.
The strategic success of any industrial player in this area would depend on a ready availability of a skilled work-force within high level technical competencies, specifically catered for the automotive environment.
Through this MSc we aim to address the knowledge-gap in the areas of machine learning, automated control strategies, connectivity, and communication infrastructure, cyber-security protocols, emerging automotive networks and robust automotive embedded systems within the context of smart, connected and autonomous vehicles.
WMG at the University of Warwick has an established legacy of leading automotive research in collaboration with industry. Our unique experimental facilities enable academics and industry practitioners to work together and include:
This MSc programme has extensive industrial support with the Industry Advisory Board consisting of Jaguar Land Rover (JLR), RDM and other industrial stakeholders.
You will need to choose four elective modules from the module list*, which should be chosen to supplement your core modules above (subject to availability). *Important, please note: the list relates to modules available in 2017/18 academic year, and should be regarded as an illustrative guide to modules available in future years.
You are required to pass nine modules in total as part of this Master's course.
Leveraging the close partnerships that WMG has with key organisations within the automotive sector, it is envisaged that your project will have an industrial sponsor, enabling you to work in close collaboration with an industry partner. This valuable experience will further your transferrable skills development, and expand your networking opportunities and understanding in a professional research and development environment.
The project is worth 50% of the final grade, and supports you in developing research and analytical skills.
Work on your project runs concurrently with your module study.
The taught component of the course consists of lectures, workshops, practicals, demonstrations, syndicate exercises, extended surgery time and reviews. Module leaders are experts in their fields and are supported by external speakers working in organisations at the forefront of their fields.
Assessment is through post module assignment (PMA) rather than exam and is based on the learning objectives of each module. Your PMA should take around 60 hours of work and consolidate the knowledge you have gained from the module.
Each module usually lasts one week. There is more information here about the course structure.
Graduates of this MSc will understand a myriad of factors contributing towards the performance and dependability of connected and autonomous vehicles and will be well placed to continue professional work within R&D.