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Masters Degrees (Affective Computing)

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The Computer Animation Master’s programme at Kent is oriented towards current industrial needs, technology and practice. It is designed to be a direct route into this high-profile, modern and creative industry, and has been developed jointly by the School and our industrial partner Framestore CFC. Read more
The Computer Animation Master’s programme at Kent is oriented towards current industrial needs, technology and practice. It is designed to be a direct route into this high-profile, modern and creative industry, and has been developed jointly by the School and our industrial partner Framestore CFC.

Develop your knowledge and understanding of the animation process, software tools, techniques and packages, and the technical aspects of working in a professional animation environment. The MSc programme offers invaluable experience of working to professional briefs and under expert supervision of professional animators to prepare you for a career in industry.

Competition is fierce in animation and visual effects and success depends on your concentration levels, constant practise and ability to grasp the essence and modern techniques of animation. Successful former students are now working in animation and animation layout roles for companies such as Sony Games and Framestore CFC on major titles in games, television and film.

Visit the website https://www.kent.ac.uk/courses/postgraduate/248/computer-animation

About the School of Engineering and Digital Arts

The School of Engineering and Digital Arts successfully combines modern engineering and technology with the exciting field of digital media. The School, which was established over 40 years ago, has developed a top-quality teaching and research base, receiving excellent ratings in both research and teaching assessments.

The School undertakes high-quality research that has had significant national and international impact, and our spread of expertise allows us to respond rapidly to new developments. Our 30 academic staff and over 130 postgraduate students and research staff provide an ideal focus to effectively support a high level of research activity. We have a thriving student population studying for postgraduate degrees in a friendly, supportive teaching and research environment.

We have research funding from the Research Councils UK, European research programmes, a number of industrial and commercial companies and government agencies including the Ministry of Defence. Our Electronic Systems Design Centre and Digital Media Hub provide training and consultancy for a wide range of companies. Many of our research projects are collaborative, and we have well-developed links with institutions worldwide.

Course structure

This intensively taught postgraduate course lasts a full year. It takes place in a dedicated computer laboratory where you have your own seat and computer for the duration of the course. The course lectures and workshops, whether led by visiting professionals or staff, are all held in this room. Demonstrations and showing of films are by means of an HD projector. By the end of the year, the lab will be where you live as much as your accommodation.

Modules

The following modules are indicative of those offered on this programme. This list is based on the current curriculum and may change year to year in response to new curriculum developments and innovation. Most programmes will require you to study a combination of compulsory and optional modules. You may also have the option to take modules from other programmes so that you may customise your programme and explore other subject areas that interest you.

EL831 - Digital Visual Art set-up (15 credits)
EL832 - Animation Principles (15 credits)
EL833 - Visual Training (15 credits)
EL837 - Professional Group Work (15 credits)
EL863 - Advanced 3D Modelling (15 credits)
EL864 - Pre-Visualisation (15 credits)
EL865 - Action in Animation (15 credits)
EL866 - Acting in Animation (15 credits)
EL830 - Computer Animation Project (60 credits)

Assessment

Each module is assessed by practical assignments. The project work is assessed on the outcome of the project itself.

Programme aims

This programme aims to:

- enable you to develop your knowledge and understanding within the field of 3D computer animation, which will equip you to become a professional in the animation and visual effects industry

- produce professionally-trained animators who are highly skilled in using state-of-the-art 3D animation software for producing animated films

- provide you with proper academic guidance and welfare support

- create an atmosphere of co-operation and partnership between staff and students, and offer you an environment where you can develop your potential

- strengthen and expand opportunities for industrial collaboration with the School of Engineering and Digital Arts.

Research areas

- Intelligent Interactions

The Intelligent Interactions group has interests in all aspects of information engineering and human-machine interactions. It was formed in 2014 by the merger of the Image and Information Research Group and the Digital Media Research Group.

The group has an international reputation for its work in a number of key application areas. These include: image processing and vision, pattern recognition, interaction design, social, ubiquitous and mobile computing with a range of applications in security and biometrics, healthcare, e-learning, computer games, digital film and animation.

- Social and Affective Computing
- Assistive Robotics and Human-Robot Interaction
- Brain-Computer Interfaces
- Mobile, Ubiquitous and Pervasive Computing
- Sensor Networks and Data Analytics
- Biometric and Forensic Technologies
- Behaviour Models for Security
- Distributed Systems Security (Cloud Computing, Internet of Things)
- Advanced Pattern Recognition (medical imaging, document and handwriting recognition, animal biometrics)
- Computer Animation, Game Design and Game Technologies
- Virtual and Augmented Reality
- Digital Arts, Virtual Narratives.

Careers

We have developed the programme with a number of industrial organisations, which means that successful students will be in a strong position to build a long-term career in this important discipline.

The School of Engineering and Digital Arts (http://www.eda.kent.ac.uk/) has an excellent record of student employability (http://www.eda.kent.ac.uk/school/employability.aspx). We are committed to enhancing the employability of all our students, to equip you with the skills and knowledge to succeed in a competitive, fast-moving, knowledge-based economy.

Graduates who can show that they have developed transferable skills and valuable experience are better prepared to start their careers and are more attractive to potential employers.

Find out how to apply here - https://www.kent.ac.uk/courses/postgraduate/apply/

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The School of Engineering and Digital Arts offers research-led degrees in a wide range of research disciplines, related to Electronic, Control and Information Engineering, in a highly stimulating academic environment. Read more
The School of Engineering and Digital Arts offers research-led degrees in a wide range of research disciplines, related to Electronic, Control and Information Engineering, in a highly stimulating academic environment. The School enjoys an international reputation for its work and prides itself in allowing students the freedom to realise their maximum potential.

Established over 40 years ago, the School has developed a top-quality teaching and research base, receiving excellent ratings in both research and teaching assessments.

We undertake high-quality research that has had significant national and international impact, and our spread of expertise allows us to respond rapidly to new developments. Our 30 academic staff and over 130 postgraduate students and research staff provide an ideal focus to effectively support a high level of research activity. There is a thriving student population studying for postgraduate degrees in a friendly and supportive teaching and research environment.

We have research funding from the Research Councils UK, European research programmes, a number of industrial and commercial companies and government agencies including the Ministry of Defence. Our Electronic Systems Design Centre and Digital Media Hub provide training and consultancy for a wide range of companies. Many of our research projects are collaborative, and we have well-developed links with institutions worldwide.

Visit the website https://www.kent.ac.uk/courses/postgraduate/262/electronic-engineering

Project opportunities

Some projects available for postgraduate research degrees (http://www.eda.kent.ac.uk/postgraduate/projects_funding/pgr_projects.aspx).

Research areas

- Communications

The Group’s activities cover system and component technologies from microwave to terahertz frequencies. These include photonics, antennae and wireless components for a broad range of communication systems. The Group has extensive software research tools together with antenna anechoic chambers, network and spectrum analysers to millimetre wave frequencies and optical signal generation, processing and measurement facilities. Current research themes include:

- photonic components
- networks/wireless systems
- microwave and millimetre-wave systems
- antenna systems
- radio-over-fibre systems
- electromagnetic bandgaps and metamaterials
- frequency selective surfaces.

- Intelligent Interactions:

The Intelligent Interactions group has interests in all aspects of information engineering and human-machine interactions. It was formed in 2014 by the merger of the Image and Information Research Group and the Digital Media Research Group.

The group has an international reputation for its work in a number of key application areas. These include: image processing and vision, pattern recognition, interaction design, social, ubiquitous and mobile computing with a range of applications in security and biometrics, healthcare, e-learning, computer games, digital film and animation.

- Social and Affective Computing
- Assistive Robotics and Human-Robot Interaction
- Brain-Computer Interfaces
- Mobile, Ubiquitous and Pervasive Computing
- Sensor Networks and Data Analytics
- Biometric and Forensic Technologies
- Behaviour Models for Security
- Distributed Systems Security (Cloud Computing, Internet of Things)
- Advanced Pattern Recognition (medical imaging, document and handwriting recognition, animal biometrics)
- Computer Animation, Game Design and Game Technologies
- Virtual and Augmented Reality
- Digital Arts, Virtual Narratives.

- Instrumentation, Control and Embedded Systems:

The Instrumentation, Control and Embedded Systems Research Group comprises a mixture of highly experienced, young and vibrant academics working in three complementary research themes – embedded systems, instrumentation and control. The Group has established a major reputation in recent years for solving challenging scientific and technical problems across a range of industrial sectors, and has strong links with many European countries through EU-funded research programmes. The Group also has a history of industrial collaboration in the UK through Knowledge Transfer Partnerships.

The Group’s main expertise lies primarily in image processing, signal processing, embedded systems, optical sensors, neural networks, and systems on chip and advanced control. It is currently working in the following areas:

- monitoring and characterisation of combustion flames
- flow measurement of particulate solids
- medical instrumentation
- control of autonomous vehicles
- control of time-delay systems
- high-speed architectures for real-time image processing
- novel signal processing architectures based on logarithmic arithmetic.

Careers

We have developed our programmes with a number of industrial organisations, which means that successful students are in a strong position to build a long-term career in this important discipline. You develop the skills and capabilities that employers are looking for, including problem solving, independent thought, report-writing, time management, leadership skills, team-working and good communication.

Kent has an excellent record for postgraduate employment: over 94% of our postgraduate students who graduated in 2013 found a job or further study opportunity within six months.

Building on Kent’s success as the region’s leading institution for student employability, we offer many opportunities for you to gain worthwhile experience and develop the specific skills and aptitudes that employers value.

Find out how to apply here - https://www.kent.ac.uk/courses/postgraduate/apply/

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This MSc teaches advanced analytical and computational skills for success in a data rich world. Read more
This MSc teaches advanced analytical and computational skills for success in a data rich world. Designed to be both mathematically rigorous and relevant, the programme covers fundamental aspects of machine learning and statistics, with potential options in information retrieval, bioinformatics, quantitative finance, artificial intelligence and machine vision.

Degree information

The programme aims to provide graduates with the foundational principles and the practical experience needed by employers in the area of machine learning and statistics. Graduates of this programme will have had the opportunity to develop their skills by tackling problems related to industrial needs or to leading-edge research.

Students undertake modules to the value of 180 credits.

The programme consists of four core modules (60 credits), four optional modules (60 credits) and a research project (60 credits). Please note that not all combinations of optional modules will be available due to timetabling restrictions.

Core modules
-Supervised Learning
-Statistical Modelling and Data Analysis
-Graphical Models or Probabilistic and Unsupervised Learning
Plus one of:
-Applied Bayesian Methods
-Statistical Design of Investigations
-Statistical Computing
-Statistical Inference

Optional modules - students select 60 credits from the following list:
-Advanced Topics in Machine Learning
-Affective Computing and Human-Robot Interaction
-Applied Bayesian Methods
-Approximate Inference and Learning in Probabilistic Models
-Computational Modelling for Biomedical Imaging
-Information Retrieval and Data Mining
-Machine Vision
-Selected Topics in Statistics
-Optimisation
-Statistical Design of Investigations
-Statistical Inference
-Statistical Natural Language Programming
-Stochastic Methods in Finance
-Stochastic Methods in Finance 2
-Advanced Topics in Statistics
-Mathematical Programming and Research Methods
-Intelligent Systems in Business

Dissertation/report
All MSc students undertake an independent research project, which culminates in a dissertation of 10,000-12,000 words.

Teaching and learning
The programme is delivered through a combination of lectures, discussions, practical sessions and project work. Student performance is assessed through unseen written examinations, coursework, practical application and the project assessment process.

Careers

There is a strong national and international demand for graduates with skills at the interface of traditional statistics and machine learning. Substantial sectors of UK industry, including leading, large companies already make extensive use of computational statistics and machine learning techniques in the course of their business activities. Globally there are a large number of very successful users of this technology, many located in the UK. Areas in which expertise in statistics and machine learning is in particular demand include; finance, banking, insurance, retail, e-commerce, pharmaceuticals, and computer security. Graduates have gone on to further study at, for example, the Universities of Cambridge, Helsinki, Chicago, as well as at UCL. The MSc is also ideal preparation for a PhD, in statistics, machine learning or a related area.

Top career destinations for this degree:
-Statistical and Algorithm Analyst, Telemetry
-Decision Scientist, Everline
-Computer Vision Researcher, Slyce
-Data Scientist, YouGov
-Research Engineer, DeepMind

Employability
Scientific experiments and companies now routinely generate vast databases and machine learning and statistical methodologies are core to their analysis. There is a considerable shortfall in the number of qualified graduates in this area internationally. CSML graduates have been in high demand for PhD positions across the sciences. In London there are many companies looking to understand their customers better who have hired our CSML graduates. Similarly graduates now work in companies in, amongst others, Germany, Iceland, France and the US in large-scale data analysis. The finance sector has also hired several graduates recently.

Why study this degree at UCL?

The Centre for Computational Statistics and Machine Learning (CSML) is a major European Centre for machine learning having coordinated the PASCAL European Network of Excellence.

Coupled with the internationally renowned Gatsby Computational Neuroscience and Machine Learning Unit, and UCL Statistical Science, this MSc programme draws on world-class research and teaching talents. The centre has excellent links with world-leading companies in internet technology, finance and related information areas.

The programme is designed to train students in both the practical and theoretical sides of machine learning. A significant grounding in computational statistics is also provided.

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The Machine Learning MSc at UCL is a truly unique programme and provides an excellent environment to study the subject. It introduces the computational, mathematical and business views of machine learning to those who want to upgrade their expertise and portfolio of skills in this domain. Read more
The Machine Learning MSc at UCL is a truly unique programme and provides an excellent environment to study the subject. It introduces the computational, mathematical and business views of machine learning to those who want to upgrade their expertise and portfolio of skills in this domain.

Degree information

Students develop an understanding of the principles underlying the development and application of new techniques in this area, alongside an awareness of, and ability to analyse the range and scope of algorithms and approaches available, and design, develop and evaluate appropriate algorithms and methods for new problems and applications.

Students undertake modules to the value of 180 credits. The programme consists of two core modules (30 credits), six optional modules (90 credits) and a research project (60 credits).

Core modules
-Supervised Learning
-Either Graphical Models
OR
-Probabilistic and Unsupervised Learning

Optional modules
-Machine Vision
-Bioinformatics
-Information Retrieval and Data Mining
-Advanced Topics in Machine Learning
-Inverse Problems in Imaging
-Affective Computing and Human-Robot Interaction
-Approximate Inference and Learning in Probabilistic Models
-Applied Machine Learning
-Computational Modelling for Biomedical Imaging
-Programming and Mathematical Methods for Machine Learning
-Statistical Natural Language Programming
-Numerical Optimisation

Dissertation/report
All MSc students undertake an independent research project which culminates in a dissertation ( maximum length of 120 pages) in the form of a project report.

Teaching and learning
The programme is delivered through a combination of lectures, seminars, class discussions and project supervision. Student performance is assessed though a combination of unseen written examination, coursework (much of which involves programming and/or data analysis), practical application, and the research project.

Careers

Graduates from this programme have an excellent employment record. Substantial sectors of UK industry, including leading, large companies already make extensive use of intelligent systems techniques in the course of their business activities, and the UK has a number of very successful developers and suppliers of the technology. Students also benefit from strong corporate and academic connections within the UCL Computer Science alumni network.

Graduates have machine learning research degrees in domains as diverse as robotics, music, psychology, bioinformatics at the universities of Basel, Cambridge, Edinburgh, Nairobi, Oxford and at UCL. Graduates have also found positions with multi national companies such as BAE Systems and BAE Detica.

Top career destinations for this degree:
-Software Engineer, Bisual
-PhD Computer Programming, Newcastle University
-Software Developer, Total Gas & Power
-Risk Analyst, National Bank of Greece
-Research Engineer, Xerox Research Centre India

Employability
Scientific experiments and companies now routinely generate vast databases and machine learning and statistical methodologies are core to their analysis. There is a considerable shortfall in the number of qualified graduates in this area internationally. Machine Learning graduates have been in high demand for PhD positions across the sciences. In London there are many companies looking to understand their customers better who have hired our graduates. Similarly graduates now work in companies in, amongst others, Germany, Iceland, France and the US in large-scale data analysis. The finance sector has also hired several graduates recently.

Why study this degree at UCL?

UCL Computer Science is recognised as a world leader in teaching and research, and our Master's programmes have some of the highest employment rates and starting salaries.

We take an experimental approach to our subject, enjoy the challenge and opportunity of entrepreneurial partnerships and place a high value on our extensive range of industrial collaborations.

This MSc is one of the few leading Master's programmes entirely dedicated to machine learning. It combines a rigorous theoretical academic framework along with specific knowledge of a variety of application fields to fast-track your commercial career or to prepare for PhD research.

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The School conducts high-quality significant national and international research and offers excellent opportunities for graduate studies, successfully combining modern engineering and technology with the exciting field of digital media. Read more
The School conducts high-quality significant national and international research and offers excellent opportunities for graduate studies, successfully combining modern engineering and technology with the exciting field of digital media. The digital media group has interests in many areas of interactive multimedia and digital film and animation.

Visit the website https://www.kent.ac.uk/courses/postgraduate/264/digital-arts

About the School of Engineering and Digital Arts

Established over 40 years ago, the School has developed a top-quality teaching and research base, receiving excellent ratings in both research and teaching assessments.

The School undertakes high-quality research (http://www.eda.kent.ac.uk/research/default.aspx) that has had significant national and international impact, and our spread of expertise allows us to respond rapidly to new developments. Our 30 academic staff and over 130 postgraduate students and research staff provide an ideal focus to effectively support a high level of research activity. There is a thriving student population studying for postgraduate degrees in a friendly and supportive teaching and research environment.

We have research funding from the Research Councils UK, European research programmes, a number of industrial and commercial companies and government agencies including the Ministry of Defence. Our Electronic Systems Design Centre and Digital Media Hub provide training and consultancy for a wide range of companies. Many of our research projects are collaborative, and we have well-developed links with institutions worldwide.

Course structure

The digital media group has interests in many areas of interactive multimedia and digital film and animation.

There is particular strength in web design and development, including e-commerce, e-learning, e-health; and the group has substantial experience in interaction design (eg, Usability and accessibility), social computing (eg, Social networking, computer mediated communication), mobile technology (eg, iPhone), virtual worlds (eg, Second Life) and video games. In the area of time-based media, the group has substantial interest in digital film capture and editing, and manipulation on to fully animated 3D modelling techniques as used in games and feature films.

Research Themes:
- E-Learning Technology (http://www.eda.kent.ac.uk/research/theme_detail.aspx?gid=1&tid=1)

- Medical Multimedia Applications and Telemedicine (http://www.eda.kent.ac.uk/research/theme_detail.aspx?gid=1&tid=2)

- Human Computer Interaction and Social Computing (http://www.eda.kent.ac.uk/research/theme_detail.aspx?gid=1&tid=3)

- Computer Animation and Digital Visual Effects (http://www.eda.kent.ac.uk/research/theme_detail.aspx?gid=1&tid=4)

- Mobile Application Design and Development (http://www.eda.kent.ac.uk/research/theme_detail.aspx?gid=1&tid=25)

- Digital Arts (http://www.eda.kent.ac.uk/research/theme_detail.aspx?gid=1&tid=26)

Research areas

- Intelligent Interactions

The Intelligent Interactions group has interests in all aspects of information engineering and human-machine interactions. It was formed in 2014 by the merger of the Image and Information Research Group and the Digital Media Research Group.

The group has an international reputation for its work in a number of key application areas. These include: image processing and vision, pattern recognition, interaction design, social, ubiquitous and mobile computing with a range of applications in security and biometrics, healthcare, e-learning, computer games, digital film and animation.

- Social and Affective Computing
- Assistive Robotics and Human-Robot Interaction
- Brain-Computer Interfaces
- Mobile, Ubiquitous and Pervasive Computing
- Sensor Networks and Data Analytics
- Biometric and Forensic Technologies
- Behaviour Models for Security
- Distributed Systems Security (Cloud Computing, Internet of Things)
- Advanced Pattern Recognition (medical imaging, document and handwriting recognition, animal biometrics)
- Computer Animation, Game Design and Game Technologies
- Virtual and Augmented Reality
- Digital Arts, Virtual Narratives.

Careers

We have developed our programmes with a number of industrial organisations, which means that successful students are in a strong position to build a long-term career in this important discipline. You develop the skills and capabilities that employers are looking for, including problem solving, independent thought, report-writing, time management, leadership skills, team-working and good communication.

Kent has an excellent record for postgraduate employment: over 94% of our postgraduate students who graduated in 2013 found a job or further study opportunity within six months.

Building on Kent’s success as the region’s leading institution for student employability, we offer many opportunities for you to gain worthwhile experience and develop the specific skills and aptitudes that employers value.

Find out how to apply here - https://www.kent.ac.uk/courses/postgraduate/apply/

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This MSc forms the second year of the dual Master's degree of the European Institute of Innovation and Technology (EIT). The programme offers an advanced ICT engineering education together with a business minor focused on innovation and entrepreneurship. Read more
This MSc forms the second year of the dual Master's degree of the European Institute of Innovation and Technology (EIT). The programme offers an advanced ICT engineering education together with a business minor focused on innovation and entrepreneurship. Students will spend their first year at one of the EIT's partner universities in Europe, and can elect to spend their second year at UCL.

See the website http://www.ucl.ac.uk/prospective-students/graduate/taught/degrees/ict-innovation-msc

Key Information

- Application dates
All applicants:
Open: 5 October 2015
Close: 15 February 2016
Fees note: UK/EU full-time fee available on request from the department

English Language Requirements

If your education has not been conducted in the English language, you will be expected to demonstrate evidence of an adequate level of English proficiency.
The English language level for this programme is: Good
Further information can be found on http://www.ucl.ac.uk/prospective-students/graduate/life/international/english-requirements .

International students

Country-specific information, including details of when UCL representatives are visiting your part of the world, can be obtained from http://www.ucl.ac.uk/prospective-students/international .

Degree Information

The thematic core foundations together with modules on Innovation and Entrepreneurship will be taught during the first year. In the second year at UCL, the programme focuses on the two thesis projects and on specialised taught modules. Students at UCL will choose either Human Computer Interaction and Design (HCID) or Digital Media Technology (DMT) as their major specialisation.

This two year dual masters degree has an overall credit value of 120 ECTS.

Students take modules to the value of 60 ECTS (150 Credits) in their second year at UCL, consisting of four taught modules (60 credits), a minor thesis (15 credits) and a master's thesis (75 credits).

- Core Modules
Technical Major: Human-Computer Interaction and Design:
Ergonomics for Design
Affective Interaction
Minor Thesis on Innovation and Entrepreneurship
Master's Thesis

Technical Major: Digital Media Technology:
Virtual Environments
Advanced Modelling, Rendering and Animation
Computational Photography and Capture
Minor Thesis on Innovation and Entrepreneurship
Master's Thesis

- Options
Technical Major: Human-Computer Interaction and Design:
Affective Computing and Human-robot Interaction
Societechnical Systems: IT and the Future of Work
Interfaces and Interactivity
Qualitative Research Methods
Virtual Environments

Technical Major: Digital Media Technology:
Machine Vision
Geometry of Images
Image Processing
Computational Modelling for Biomedical Imaging
Acquisition and Processing of 3D Geometry
Multimedia Systems
Network and Application Programming
Interaction Design
Professional Practice

- Dissertation/report
All MSc students undertake a minor thesis and a master's thesis, in collaboration with an external partner. For the master's thesis, students will spend at least two months in the external partner's environment.

Teaching and Learning

The programme is delivered through a combination of lectures, discussions, practical sessions, case studies, problem-based learning and project work. Assessment is through coursework assignments, unseen examinations and the two thesis projects.

Further information on modules and degree structure available on the department web site ICT Innovation MSc http://www.cs.ucl.ac.uk/admissions/msc_ict_innovation/

Funding

Scholarships relevant to this department are displayed (where available) below. For a comprehensive list of the funding opportunities available at UCL, including funding relevant to your nationality, please visit the Scholarships and Funding website http://www.ucl.ac.uk/prospective-students/scholarships .

- Brown Family Bursary - NOW CLOSED FOR 2015/16 ENTRY
Value: £15,000 (1 year)
Eligibility: UK students
Criteria: Based on both academic merit and financial need

- Computer Science Excellence Scholarships
Value: £4,000 (1)
Eligibility: UK, EU students
Criteria:

More scholarships are listed on the Scholarships and Funding website http://www.ucl.ac.uk/prospective-students/scholarships

Careers

Graduates of this programme will have the key skills in innovation and entrepreneurship necessary for the international market, together with a solid foundation in the technical topics that drive the modern technological economy.

Why study this degree at UCL?

The EIT Digital Master School is a European initiative designed to turn Europe into a global leader in ICT innovation, fostering a partnership between leading companies, research centres and technical universities in Europe.

The school offers two-year programmes where you can choose two universities in two different European institutes to build a curriculum of your choice based on your skills and interest. We offer double degrees, which combine technical competence with a set of skills in innovation and entrepreneurship. While you get an excellent theoretical education, you also get the opportunity to work with leading European research institutes and leading business partners.

Student / staff ratios › 200 staff including 120 postdocs › 650 taught students › 175 research students

Application and next steps

- Applications
Students are advised to apply as early as possible due to competition for places. Those applying for scholarship funding (particularly overseas applicants) should take note of application deadlines.

- Who can apply?
This programme is suitable for students with a relevant degree who wish to develop key skills in innovation and entrepreneurship together with an advanced education in ICT engineering, for a future career or further study in this field.

The admission procedure for the EIT ICT Labs Master's programme is organised centrally from Sweden by the KTH Admissions Office. Please read the admission requirements and application instructions before sending your documents. For further details of how to apply please visit http://www.eitictlabs.masterschool.eu/programme/application-admission/application-instructions.
Please note that applications after the deadline may be accepted. Late applications will be processed subject to time, availability and resources.

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Understanding all aspects of Human-Robot interaction. the programming that coordinates a robot’s actions with human action as well the human appreciation and trust in the robot. Read more
Understanding all aspects of Human-Robot interaction: the programming that coordinates a robot’s actions with human action as well the human appreciation and trust in the robot.
At present, there are many sensors and actuators in every device – so they may become embedded in a physical reality. For robots that move around in a specific setting there is a pressing need for the development of proper methods of control and joint-action. The embedded, embodied nature of human cognition is an inspiration for this, and vice versa. Computational modelling of such tasks can give insight into the nature of human mental processing. In the Master’s specialisation in Robot Cognition you’ll learn all about the sensors, actuators and the computational modelling that connects them.
Making sense of sensor data – developing artificial perception – is no trivial task. The perception, recognition and even appreciation of sound stimuli for speech and music (i.e. auditory scene analysis) require modelling and representation at many levels and the same holds for visual object recognition and computer vision. In this area, vocal and facial expression recognition (recognition of emotion from voices and faces) is a rapidly growing application area. In the area of action and motor planning, sensorimotor integration and action, there are strong links with research at the world-renowned Donders Centre for Cognition.
At Radboud University we also look beyond the technical side of creating robots that can move, talk and interpret emotions as humans do. We believe that a robot needs to do more than simply function to its best ability. A robot that humans distrust will fail even if it is well programmed. Culture also plays a role in this; people in Japan are more open to the possibilities of robots than in, for example, the Netherlands. We will teach you how to evaluate humans’ attitudes towards a robot in order to use that information to create robots that will be accepted and trusted and therefore perform even better.

See the website http://www.ru.nl/masters/ai/robot

Why study Robot Cognition at Radboud University?

- We offer a great mix of technical and social aspects of robot cognition.

- This programme focuses on programming robot behaviours and evaluating them rather than building the robots themselves. We teach you to programme robots that will be used in close contact with human beings, for example in healthcare and education, rather than in industry.

- Our cognitive focus leads to a highly interdisciplinary AI programme where students gain skills and knowledge from a number of different areas such as mathematics, computer science, psychology and neuroscience combined with a core foundation of artificial intelligence.

- This specialisation offers plenty of room to create a programme that meets your own academic and professional interests.

- Together with the world-renowned Donders Institute, the Max Planck Institute and various other leading research centres in Nijmegen, we train our students to become excellent researchers in AI.

- To help you decide on a research topic there is a semi-annual Thesis Fair where academics and companies present possible project ideas. Often there are more project proposals than students to accept them, giving you ample choice. We are also open to any of you own ideas for research.

- Our AI students are a close-knit group; they have their own room in which they often get together to interact, debate and develop their ideas. Every student also receives personal guidance and supervision from a member of our expert staff.

Our research in this field

The programme is closely related to the research carried out in the internationally renowned Donders Institute for Brain, Cognition and Behaviour. This institute has several unique facilities for brain imaging using EEG, fMRI and MEG. You could also cooperate with the Behavioural Science Institute and work in its Virtual Reality Laboratory, which can be used to study social interaction between humans and avatars.

An example of a possible thesis subject:
- Engaging human-robot interactions in healthcare for children and/or the elderly
Social robots are often deployed with 'special' user groups such as children and elderly people. Developing and evaluating robot behaviours for these user groups is a challenge as a proper understanding of their cognitive and social abilities is needed. Depending on the task, children for example need to be engaged and encouraged in a different way than adults do. What are effective robot behaviours and strategies to engage children and/or elderly people? How can these robot behaviours be evaluated in a proper way?

Career prospects

Our Artificial Intelligence graduates have excellent job prospects and are often offered a job before they have actually graduated. Many of our graduates go on to do a PhD either at a major research institute or university with an AI department. Other graduates work for companies interested in cognitive design and research. Examples of companies looking for AI experts with this specialisation: Philips, Siemens, Honda, Mercedes, Google. Some students have even gone on to start their own companies.

Job positions

Examples of jobs that a graduate of the specialisation in Robot Cognition could get:
- PhD Researcher on Cognitive-Affective Modelling for Social Robots
- PhD Researcher on Automatic analysis of human group behaviour in the presence of robots
- PhD Researcher on Automatic analysis of affective quality of conversations in human-robot interaction
- Advisor and innovation manager in the healthcare industry
- Social robotics and affective computing for robots expressing emotions
- Developer of control algorithms for using optic flow in drones
- Advisor for start-up company on developing new uses for tactile displays
- Team member in design of emotion recognition and training for autistic children

Internship

Half of your second year consists of an internship, giving you plenty of hands-on experience. We encourage students to do this internship abroad, although this is not mandatory. We do have connections with companies abroad, for example in China, Finland and the United States.

See the website http://www.ru.nl/masters/ai/robot

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Technology Studies Education provides a forum for exploring and studying information and communication technologies (ICT), new media, and the philosophy of technology. Read more

Program Overview

Technology Studies Education provides a forum for exploring and studying information and communication technologies (ICT), new media, and the philosophy of technology. Curriculum, pedagogy, research, and development interests of faculty and students include affective computing, cyberculture and cyborg relations, digital ecology and diversity, distributed cognition, gaming, ICT integration in K–16 formal and informal learning environments (face-to-face, hybrid, and online distance education), intellectual property, open source, and cultural studies. The program offers a common core of courses, a range of electives, and a variety of professional education opportunities.

Quick Facts

- Degree: Master of Arts (research-based), Master of Education (course-based)
- Specialization: Media and Technology Studies Education
- Subject: Education
- Mode of delivery: On campus
- Faculty: Faculty of Education

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The graduate programs (M.Ed. and M.A) in Media and Technology Studies Education are part of the graduate offerings in the Department or Curriculum and Pedagogy. Read more

Program Overview

The graduate programs (M.Ed. and M.A) in Media and Technology Studies Education are part of the graduate offerings in the Department or Curriculum and Pedagogy. Media and Technology Studies provides a forum for exploring and studying information and communication technologies (ICT), new media, and the philosophy of technology. Curriculum, pedagogy, research, and development interests of faculty and students include affective computing, cyberculture and cyborg relations, digital ecology and diversity, distributed cognition, gaming, ICT integration in K-16 formal and informal learning environments (face-to-face, hybrid, and online distance education), intellectual property, open source, and cultural studies. The program offers a common core of courses, a range of electives, and a variety of professional education opportunities.

The Department offers a Sub-specialization in Human-Computer Interaction (HCI) in conjunction with the Media and Graphics Interdisciplinary Centre (MAGIC), which is available to students in the Media and Technology Studies Education program.

Quick Facts

- Degree: Master of Education
- Specialization: Technology Studies Education
- Subject: Education
- Mode of delivery: On campus
- Program components: Coursework + Major Project/Essay required
- Faculty: Faculty of Education

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Data Science brings together computational and statistical skills for data-driven problem solving. Read more
Data Science brings together computational and statistical skills for data-driven problem solving. This rapidly expanding area includes machine learning, deep learning, large-scale data analysis and has applications in e-commerce, search/information retrieval, natural language modelling, finance, bioinformatics and related areas in artificial intelligence.

Degree information

The programme comprises core machine learning methodology and an introduction to statistical science, combined with a set of more specialised and advanced options covering computing and statistical modelling. Projects are offered both within UCL Computer Science and from a wide range of industry partners.

Students undertake modules to the value of 180 credits.

The programme consists of three compulsory modules (45 credits), five optional modules (75credits) and a dissertation/report (60 credits).

Core modules
-Applied Machine Learning
-Introduction to Supervised Learning
-Introduction to Statistical Data Science

Optional modules - students choose a minimum of 30 credits and a maximum of 60 credits from the following optional modules:
-Cloud Computing (Birkbeck)
-Machine Vision
-Information Retrieval & Data Mining
-Statistical Natural Language Processing
-Web Economics

Students choose a minimum of 0 credits and a maximum of 30 credits from these optional Statistics modules:
-Statistical Design of Investigations
-Applied Bayesian Methods
-Decision & Risk

Students choose a minimum of 15 credits and a maximum of 15 credits from these elective modules:
-Supervised Learning
-Graphical Models
-Bioinformatics
-Affective Computing and Human-Robot Interaction
-Computational Modelling for Biomedical Imaging
-Stochastic Systems
-Forecasting

Dissertation/report
All students undertake an independent research project which culminates in a dissertation of 10,000-12,000 words.

Teaching and learning
The programme is delivered though a combination of lectures, seminars, class discussions and project supervision. Student performance is assessed through a combination of unseen written examination, coursework (much of which involves programming and/or data analysis), practical application, and the research project.

Careers

Data science professionals are increasingly sought after as the integration of statistical and computational analytical tools becomes more essential to organisations. A thorough understanding of the fundamentals required from the best practitioners, and this programme's broad base, assists data scientists to adapt to rapidly evolving goals. This is a new degree and information on graduate destinations is not currently available. However, MSc graduates from across the department frequently find roles with major tech and finance companies including:
-Google Deepmind
-Microsoft Research
-Dunnhumby
-Index Ventures
-Last.fm
-Cisco
-Deutsche Bank
-IBM
-Morgan Stanley

Why study this degree at UCL?

The 2014 Research Excellence Framework ranked UCL first in the UK for computer science. 61% of its research work is rated as world-leading and 96% as internationally excellent.

UCL Computer Science staff have research interests ranging from foundational machine learning and large-scale data analysis to commercial aspect of business intelligence. Our extensive links to companies provide students with opportunities to carry out the research project with an industry partner.

The department also enjoys strong collaborative relationships across UCL; and exposure to interdisciplinary research spanning UCL Computer Science and UCl Statistical Science will provide students with a broad perspective of the field. UCL is home to regular machine learning masterclasses and big data seminars.

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Data science brings together computational and statistical skills for data-driven problem solving, which is in increasing demand in fields such as marketing, pharmaceutics, finance and management. Read more
Data science brings together computational and statistical skills for data-driven problem solving, which is in increasing demand in fields such as marketing, pharmaceutics, finance and management. This MSc will equip students with the analytical tools to design sophisticated technical solutions using modern computational methods and with an emphasis on rigorous statistical thinking.

Degree information

The programme combines training in core statistical and machine learning methodology, beginning at an introductory level, with a range of optional modules covering more specialised knowledge in statistical computing and modelling. Students choosing the statistics specialisation will take one compulsory module and up to two additional modules from computer science, with the remaining modules (including the research project) taken mainly from within UCL Statistical Science.

Students undertake modules to the value of 180 credits.

The programme consists of four core modules (60 credits), four optional modules (60 credits) and a research dissertation/report (60 credits).

Core modules
-Introduction to Statistical Data Science
-Introduction to Supervised Learning
-Statistical Design of Investigations
-Statistical Computing

Optional modules - st least two from a choice of Statistical Science modules including:
-Applied Bayesian Methods
-Decision & Risk
-Factorial Experimentation
-Forecasting
-Quantitative Modelling of Operational Risk and Insurance Analytics
-Selected Topics in Statistics
-Stochastic Methods in Finance I
-Stochastic Methods in Finance II
-Stochastic Systems

Up to two from a choice of Computer Science modules including:
-Affective Computing and Human-Robot Interaction
-Graphical Models
-Statistical Natural Language Processing
-Information Retrieval & Data Mining

Dissertation/report
All students undertake an independent research project, culminating in a dissertation usually comprising 10,000-12,000 words. Workshops running during the teaching terms provide preparation for this project and cover the communication of statistics.

Teaching and learning
The programme is delivered through a combination of lectures, tutorials and classes, some of which are dedicated to practical work. Assessment is through written examination and coursework. The research project is assessed through the dissertation and a 15-minute presentation.

Careers

Graduates from UCL Statistical Science typically enter professional employment across a broad range of industry sectors or pursue further academic study.

The Data Science MSc is a new programme with the first cohort of students due to graduate in 2017. Recent career destinations for graduates of the related Statistics MSc include:
-Towers Watson, Actuary Analyst
-Proctor & Gamble, Statistician
-Ernst & Young, Audit Associate
-Collinson Group, Insurance Analyst
-UCL, PhD Statistical Science

Employability
Data science professionals will be highly sought after as the integration of statistical and computational analytical tools becomes increasingly essential in all kinds of organisations and enterprises. A solid understanding of the fundamentals is to be expected from the best practitioners. For instance, in applications in marketing, the healthcare industry and banking, computational skills should go along with statistical expertise as graduate level. Data scientists should have a broad background so that they will be able to adapt themselves to rapidly evolving challenges. Recent graduates from the related Statistics MSc have been offered positions as research analysts or consultants, and job opportunities in these areas are increasing.

Why study this degree at UCL?

UCL Statistical Science has a broad range of research interests, but has particular strengths in the area of computational statistics and in the interface between statistics and computer science.

UCL's Centre for Computational Statistics and Machine Learning, in which many members of the department are active, has a programme of seminars, masterclasses and other events. UCL's Centre for Data Science and Big Data Institute are newer developments, again with strong involvement of the department, where emphasis is on research into big data problems.

UCL is one of the founding members of the Alan Turing Institute, and both UCL Statistical Science and UCL Computer Science will be playing major roles in this exciting new development which will make London a major focus for big data research.

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Robotics and autonomous systems (RAS) are set to shape innovation in the 21st century, underpinning research in a wide range of challenging areas. Read more
Robotics and autonomous systems (RAS) are set to shape innovation in the 21st century, underpinning research in a wide range of challenging areas: the ageing population, efficient health care, safer transport, and secure energy. The UCL edge in scientific excellence, industrial collaboration and cross-sector activities make it ideally placed to drive IT robotics and automation education in the UK.

Degree information

The programme provides an overview of robotic and computational tools for robotics and autonomous systems as well as their main computational components: kinetic chains, sensing and awareness, control systems, mapping and navigation. Optional modules in machine learning, human-machine interfaces and computer vision help students grasp fields related to robotics more closely, while the project thesis allows students to focus on a specific research topic in depth.

Students undertake modules to the value of 180 credits.

The programme consists of four core modules (60 credits), two optional modules (30 credits), two elective modules (30 credits), and a dissertation/report (60 credits).

Core modules
-Robotic Control Theory and Systems
-Robotic Sensing, Manipulation and Interaction
-Robotic Systems Engineering
-Robotic Vision and Navigation

Optional modules
-Acquisition and Processing of 3D Geometry
-Affective Computing and Human-Robot Interaction
-Artificial Intelligence and Neural Computing
-Image Processing
-Inverse Problems in Imaging
-Machine Vision
-Mathematical Methods, Algorithmics and Implementations
-Probabilistic and Unsupervised Learning
-Research Methods and Reading
-Supervised Learning
-Other selected modules available within UCL Computer Science
-Students also choose two elective MSc modules from across UCL Computer Science, UCL Medical Physics & Biomedical Engineering, UCL Mechanical Engineering and UCL Bartlett School of Architecture.

Dissertation/report
All students undertake an independent research project which culminates in a dissertation of 30,000 words.

Teaching and learning
Teaching is delivered by lectures, tutorials, practical sessions, projects and seminars. Assessment is through examination, individual and group projects and presentations, and design exercises.

Careers

Robotics is a growing field encompassing many technologies with applications across different industrial sectors, and spanning manufacturing, security, mining, design, transport, exploration and healthcare. Graduates from our MSc programme will have diverse job opportunities in the international marketplace with their knowledge of robotics and the underpinning computational and analytical fundamentals that are highly valued in the established and emerging economies. Students will also be well placed to undertake PhD studies in robotics and computational research specific to robotics but translational across different analytical disciplines or applied fields that will be influenced by new robotic technologies and capabilities.

Employability
This programme prepares students to enter a robotics-related industry or any other occupation requiring engineering or analytical skills. Graduates with skills to develop new robotics solutions and solve computational challenges in automation are likely to be in demand globally.

Why study this degree at UCL?

UCL was ranked first in the UK for computer science and informatics in the recent Research Excellence Framework (REF).

With the external project involvement anticipated, students on this programme will have the opportunity to interact and collaborate with key companies in the industry - Airbus, Shadow Hand, OC Robotics and Intuitive Surgical - and work on real-world problems through industry-supported projects.

Recent investment across UCL in the Faculty of Engineering and The Bartlett Faculty of the Built Environment has created the infrastructure for an exciting robotics programme, which will be interdisciplinary and unique within the UK and Europe.

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An MSc-level conversion programme for those with first degrees in numerate disciplines (e.g. Maths, Physics, others with some mathematics to pre-university level should enquire). Read more
An MSc-level conversion programme for those with first degrees in numerate disciplines (e.g. Maths, Physics, others with some mathematics to pre-university level should enquire). The programme targets producing engineers with the knowledge and skills required for working in the communications industry on programmable hardware, in particular. There is a high demand for people to fill such roles in communications and test & measure equipment vendors, and in many smaller companies developing devices for the internet of things.

The huge growth of interconnected devices expected in the Internet of Things and the goals of flexible, high-speed wireless connections for 5G mobile networks and beyond, require programmable, embedded electronics to play a vital role. From the development of small, intelligence sensors to the design of large-scale network hardware that can be functionally adaptive in software-defined networking, there is a huge demand for advanced embedded electronics knowledge and skills in the communications sector.

Visit the website https://www.kent.ac.uk/courses/postgraduate/1223/embedded-communications-engineering

About the School of Engineering and Digital Arts

The School of Engineering and Digital Arts successfully combines modern engineering and technology with the exciting field of digital media.

Established over 40 years ago, the School has developed a top-quality teaching and research base, receiving excellent ratings in both research and teaching assessments.

The School undertakes high-quality research that has had significant national and international impact, and our spread of expertise allows us to respond rapidly to new developments. Our 30 academic staff and over 130 postgraduate students and research staff provide an ideal focus to effectively support a high level of research activity. There is a thriving student population studying for postgraduate degrees in a friendly and supportive teaching and research environment.

Modules

The following modules are indicative of those offered on this programme. This list is based on the current curriculum and may change year to year in response to new curriculum developments and innovation. Most programmes will require you to study a combination of compulsory and optional modules. You may also have the option to take modules from other programmes so that you may customise your programme and explore other subject areas that interest you.

EL829 - Embedded Real-Time Operating Systems (15 credits)
EL849 - Research Methods & Project Design (30 credits)
EL893 - Reconfigurable Architectures (15 credits)
EL896 - Computer and Microcontroller Architectures (15 credits)
EL822 - Communication Networks (15 credits)
EL827 - Signal & Communication Theory II (15 credits)
EL871 - Digital Signal Processing (DSP) (15 credits)
EL872 - Wireless/Mobile Communications (15 credits)
EL873 - Broadband Networks (15 credits)
EL890 - MSc Project (60 credits)

Research areas

- Communications

The Group’s activities cover system and component technologies from microwave to terahertz frequencies. These include photonics, antennae and wireless components for a broad range of communication systems. The Group has extensive software research tools together with antenna anechoic chambers, network and spectrum analysers to millimetre wave frequencies and optical signal generation, processing and measurement facilities. Current research themes include:

- photonic components
- networks/wireless systems
- microwave and millimetre-wave systems
- antenna systems
- radio-over-fibre systems
- electromagnetic bandgaps and metamaterials
- frequency selective surfaces.

- Intelligent Interactions:

The Intelligent Interactions group has interests in all aspects of information engineering and human-machine interactions. It was formed in 2014 by the merger of the Image and Information Research Group and the Digital Media Research Group.

The group has an international reputation for its work in a number of key application areas. These include: image processing and vision, pattern recognition, interaction design, social, ubiquitous and mobile computing with a range of applications in security and biometrics, healthcare, e-learning, computer games, digital film and animation.

- Social and Affective Computing
- Assistive Robotics and Human-Robot Interaction
- Brain-Computer Interfaces
- Mobile, Ubiquitous and Pervasive Computing
- Sensor Networks and Data Analytics
- Biometric and Forensic Technologies
- Behaviour Models for Security
- Distributed Systems Security (Cloud Computing, Internet of Things)
- Advanced Pattern Recognition (medical imaging, document and handwriting recognition, animal biometrics)
- Computer Animation, Game Design and Game Technologies
- Virtual and Augmented Reality
- Digital Arts, Virtual Narratives.

- Instrumentation, Control and Embedded Systems:

The Instrumentation, Control and Embedded Systems Research Group comprises a mixture of highly experienced, young and vibrant academics working in three complementary research themes – embedded systems, instrumentation and control. The Group has established a major reputation in recent years for solving challenging scientific and technical problems across a range of industrial sectors, and has strong links with many European countries through EU-funded research programmes. The Group also has a history of industrial collaboration in the UK through Knowledge Transfer Partnerships.

The Group’s main expertise lies primarily in image processing, signal processing, embedded systems, optical sensors, neural networks, and systems on chip and advanced control. It is currently working in the following areas:

- monitoring and characterisation of combustion flames
- flow measurement of particulate solids
- medical instrumentation
- control of autonomous vehicles
- control of time-delay systems
- high-speed architectures for real-time image processing
- novel signal processing architectures based on logarithmic arithmetic.

Careers

The programme targets producing engineers with the knowledge and skills required for working in the communications industry on programmable hardware, in particular. There is a high demand for people to fill such roles in communications and test & measure equipment vendors, and in many smaller companies developing devices for the internet of things.

Kent has an excellent record for postgraduate employment: over 94% of our postgraduate students who graduated in 2013 found a job or further study opportunity within six months.

We have developed our programmes with a number of industrial organisations, which means that successful students are in a strong position to build a long-term career in this important discipline. You develop the skills and capabilities that employers are looking for, including problem solving, independent thought, report-writing, time management, leadership skills, team-working and good communication.

Find out how to apply here - https://www.kent.ac.uk/courses/postgraduate/apply/

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Interactive narrative techniques should be made compatible with the requirements of dialogue generation to support some of the aesthetic components of traditional media (intended as including humour, witticisms, etc.), however the challenges ahead remain complex. Read more
Interactive narrative techniques should be made compatible with the requirements of dialogue generation to support some of the aesthetic components of traditional media (intended as including humour, witticisms, etc.), however the challenges ahead remain complex.

This project aims to investigate new methodologies for the purpose of automatic generation of narratively meaningful dialogues between a virtual character and a human. We will explore a range of approaches at the interface between affective embodied conversational agents and interactive storytelling for a natural interaction with a human interlocutor. One of the remaining challenges in narrative dialogue generation is how a conversational agent can adapt to its interlocutor by means of modifying its dialogue intentions and information provisions as part of the on-going narrative context. This project will explore and evaluate existing techniques in affective computing, agent-based communication and narrative systems related to the generation of real-time interactive conversations between a virtual agent and a human, as well as devising specific approaches through the development of a prototype which will provide the test-bed for a large-scale user evaluation for validation.

How to apply: Applications are made via our website using the Apply Online button below. If you have an enquiry about this project please contact us via the Email NOW button below, however your application will only be processed once you have submitted an application form as opposed to emailing your CV to us. Application deadline: 24 July 2017.

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This successful BPS accredited programme, drawing on a multidisciplinary approach to health, covers the main areas of sickness and health psychology, as well as the methodologies for conducting research in primary, secondary and tertiary healthcare settings. Read more

Overview

This successful BPS accredited programme, drawing on a multidisciplinary approach to health, covers the main areas of sickness and health psychology, as well as the methodologies for conducting research in primary, secondary and tertiary healthcare settings.

The course is one of the only accredited MSc Health Psychology programmes offering a placement. Our placement is 4-months in duration, and students are fully supported before and during their placement. Our dedicated placements team ensure students are not only allocated placements, but are prepared before starting their placement through seminars and meetings with their placement tutor. This support continues over the 4-months, making sure students are happy and getting the most from their placement experience. Watch our placement video to find out more about the MSc Health Psychology placement and what our students think.

Units include: introduction to health and health beliefs; biopsychosocial mechanisms in health; health, communication and context; managing ill-health; health psychology in practice; research design and statistics in health; and a dissertation.

For more information: http://www.bath.ac.uk/psychology/postgraduate/health

Further information can be found in the Programme & Unit Catalogue (http://www.bath.ac.uk/catalogues/2015-2016/ps/ps-proglist-pg.html#A).

About the department

The rapidly expanding Department of Psychology (http://www.bath.ac.uk/psychology/) has a distinctive research profile and a long-standing record of cutting-edge, theoretically-informed research in applied aspects of psychology. It has a strong tradition of interdisciplinary work and collaborates with other departments in the University of Bath, local and national institutions, and international networks.

Facilities and equipment:
The Department of Psychology is part of the Faculty of Humanities and Social Sciences. We currently have 300 undergraduates and 90 postgraduates in our department who benefit from:

- an enthusiastic and approachable staff team with 21 academics, 9 administrative or technical support staff and 2 research officers;
- a lively research environment; and
- outstanding computing facilities;
- regular seminar programmes establish a sense of community.

The Department of Psychology (the main foyer, Department Office and Reception Hatch) is based in building 2 South where most lecturers and support staff have offices. Student pigeonholes, assignment submission boxes and noticeboards are also in this building. Some staff and our postgraduate research students are located in 6 West (mainly level 0), 5 South (not open to visitors) and 1 West 3.12 (for MPhil/PhD queries).

International and industrial links:
The Cognition, Affective Science and Technology Laboratories (CASTL) group has collaborative links with human computer interaction groups within the UK (e.g. London Knowledge Lab and The Mixed Reality Lab at Nottingham) with education groups in America (at Harvard) and with industrial partners on collaborative research projects including Sciencescope (an educational sensor design company), Vodafone and BT.

The Social and Cultural Psychology group is allied with the Institute for Sustainable Energy and the Environment and the National Children's Bureau. All groups are supported by research grants from research councils such as the ESRC and EPSRC.

The Health Psychology group benefits from both a theoretical, methodological and applied focus and has strong interdisciplinary research links with the Department of Pharmacy (research on psychoneuroimmunology and stress, pain and pain management, well-being and quality of life) and the Department of Social & Policy Sciences (work on coping responses and substance abuse). They are supported by links with: the Royal United Hospital (RUH); Royal National Hospital for Rheumatic Diseases (RNHRD); Transition to School Research Project-funded by the Economic and Social Reseach Council (ESRC); the WHO Field Centre for the Study of Quality of Life (WHO-QOL) (based within the department); Wellbeing in Developing Countries Research group; Centre of Death and Society; Department for Health (incorporating the Mental Health Research & Development Unit (MHRDU), the Centre for Pain Reseach (CPR) and the Division of Sport & Exercise Science).

Main areas of research

- Behaviour Change and Mental Health Interventions (http://www.bath.ac.uk/psychology/research/behaviour-change-mental-health-interventions/)
- BioSocial, Cognitive-Affective Psychology (http://www.bath.ac.uk/psychology/research/biosocial-cognitive-affective-psychology/)
- Digital Behaviour and Change (http://www.bath.ac.uk/psychology/research/digital-behaviour-change/)
- Identities in Social and Digital Contexts (http://www.bath.ac.uk/psychology/research/identities-social-digital-contexts/)

Find out how to apply here - http://www.bath.ac.uk/hss/graduate-school/taught-programmes/how-to-apply/

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