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The Medical Physics and Bioengineering MRes provides structured training in this diverse and multi-disciplinary field and students may subsequently progress to an MPhil/PhD as part of a Doctoral Training Programme. Read more
The Medical Physics and Bioengineering MRes provides structured training in this diverse and multi-disciplinary field and students may subsequently progress to an MPhil/PhD as part of a Doctoral Training Programme.

See the website http://www.ucl.ac.uk/prospective-students/graduate/taught/degrees/medical-physics-bioengineering-mres

Key Information

- Application dates
All applicants:
Open: 5 October 2015
Close: 29 July 2016

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: Standard
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 programme covers all forms of ionising and non-ionising radiation commonly used in medicine and applies it to the areas of imaging and treatment. The programme involves Master's level modules chosen from a wide range offered by the department and a research project. Good performance in the MRes will lead to entry into the 2nd year of the Doctoral Training Programme where the research project is continued.

Students undertake modules to the value of 180 credits.

The programme consists of four optional modules and a research project.

- Core Modules
There are no core modules for this programme.

- Options
Students choose four optional modules from the following:
Ionising Radiation Physics: Interactions and Dosimetry
Medical Imaging
Clinical Practice
Treatment with Ionising Radiation
Medical Electronics and Control
Bioengineering
Optics in Medicine
Computing in Medicine
Medical Devices and Applications
Foundations and Anatomy and Scientific Computing
Image Processing
Computational Modelling in Biomedical Imaging
Programming Foundations for Medical Image Analysis
Information Processing in Medical Imaging
Image-Directed Analysis and Therapy

- Dissertation/report
All students undertake a research project.

Further information on modules and degree structure available on the department web site Medical Physics and Bioengineering MRes http://www.ucl.ac.uk/medphys/prospective-students/phd/dtp

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 .

Careers

Our graduates typically find work in academia, the NHS, and in industry

Why study this degree at UCL?

The department is one of the largest medical physics and bioengineering departments in Europe, with links to a large number of active teaching hospitals. We have arguably the widest range of research of any similar department, and work closely with other world-leading institutions.

Students on the programme will form part of an interactive network of researchers across many disciplines and will benefit from the strengths of UCL in the healthcare field.

Student / staff ratios › 144 staff including 110 postdocs › 107 taught students › 135 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?
The programme is suitable either for students wishing to study for a stand-alone MRes in Medical Physics & Bioengineering or for students planning progression to a Doctoral Training Programme.

What are we looking for?
When we assess your application we would like to learn:
- why you want to study Medical Physics and Bioengineering at graduate level
- why you want to study Medical Physics and Bioengineering at UCL
- what particularly attracts you to this programme
- how your personal, academic and professional background meets the demands of a challenging programme
- where you would like to go professionally with your degree

Together with essential academic requirements, the personal statement is your opportunity to illustrate whether your reasons for applying to this programme match what the programme will deliver.

For more information see the Applications page http://www.ucl.ac.uk/prospective-students/graduate/apply .

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If you are intrigued by the acquisition, processing, analysis and understanding of computer vision, this Masters is for you. The programme is offered by Surrey's Department of Electrical and Electronic Engineering, recognised for world-leading research in multimedia signal processing and machine learning. Read more
If you are intrigued by the acquisition, processing, analysis and understanding of computer vision, this Masters is for you.

The programme is offered by Surrey's Department of Electrical and Electronic Engineering, recognised for world-leading research in multimedia signal processing and machine learning.

PROGRAMME OVERVIEW

This degree provides in-depth training for students interested in a career in industry or in research-oriented institutions focused on image and video analysis, and deep learning.

State-of-the-art computer-vision and machine-learning approaches for image and video analysis are covered in the course, as well as low-level image processing methods.

Students also have the chance to substantially expand their programming skills through projects they undertake.

PROGRAMME STRUCTURE

This programme is studied full-time over 12 months and part-time over 48 months. It consists of eight taught modules and a standard project.

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.
-Digital Signal Processing A
-Object Oriented Design and C++
-Image Processing and Vision
-Space Robotics and Autonomy
-Satellite Remote Sensing
-Computer Vision and Pattern Recognition
-AI and AI Programming
-Advanced Signal Processing
-Image and Video Compression
-Standard Project

EDUCATIONAL AIMS OF THE PROGRAMME

The taught postgraduate degree programmes of the Department of Electronic Engineering 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:
-Attract well-qualified entrants, with a background in Electronic Engineering, Physical Sciences, Mathematics, Computing and Communications, from the UK, Europe and overseas.
-Provide participants with advanced knowledge, practical skills and understanding applicable to the MSc degree
-Develop participants' understanding of the underlying science, engineering, and technology, and enhance their ability to relate this to industrial practice
-Develop participants' critical and analytical powers so that they can effectively plan and execute individual research/design/development projects
-Provide a high level of flexibility in programme pattern and exit point
-Provide students with an extensive choice of taught modules, in subjects for which the Department has an international and UK research reputation

Intended capabilities for MSc graduates
-Know, understand and be able to apply the fundamental mathematical, scientific and engineering facts and principles that underpin computer vision, machine learning as well as how they can be related to robotics
-Be able to analyse problems within the field computer vision and more broadly in electronic engineering and find solutions
-Be able to use relevant workshop and laboratory tools and equipment, and have experience of using relevant task-specific software packages to perform engineering tasks
-Know, understand and be able to use the basic mathematical, scientific and engineering facts and principles associated with the topics within computer vision, machine learning
-Be aware of the societal and environmental context of his/her engineering activities
-Be aware of commercial, industrial and employment-related practices and issues likely to affect his/her engineering activities
-Be able to carry out research-and-development investigations
-Be able to design electronic circuits and electronic/software products and systems

Technical characteristics of the pathway
This programme in Computer Vision, Robotics and Machine Learning aims to provide a high-quality advanced training in aspects of computer vision for extracting information from image and video content or enhancing its visual quality using machine learning codes.

Computer vision technology uses sophisticated signal processing and data analysis methods to support access to visual information, whether it is for business, security, personal use or entertainment. The core modules cover the fundamentals of how to represent image and video information digitally, including processing, filtering and feature extraction techniques.

An important aspect of the programme is the software implementation of such processes. Students will be able to tailor their learning experience through selection of elective modules to suit their career aspirations.

Key to the programme is cross-linking between core methods and systems for image and video analysis applications. The programme has strong links to current research in the Department of Electronic Engineering’s Centre for Vision, Speech and Signal Processing.

PROGRAMME LEARNING OUTCOMES

The Department's taught postgraduate programmes are designed to enhance the student's technical knowledge in the topics within the field that he/she has chosen to study, and to contribute to the Specific Learning Outcomes set down by the Institution of Engineering and Technology (IET) (which is the Professional Engineering body for electronic and electrical engineering) and to the General Learning Outcomes applicable to all university graduates.

General transferable skills
-Be able to use computers and basic IT tools effectively
-Be able to retrieve information from written and electronic sources
-Be able to apply critical but constructive thinking to received information
-Be able to study and learn effectively
-Be able to communicate effectively in writing and by oral presentations
-Be able to present quantitative data effectively, using appropriate methods

Time and resource management
-Be able to manage own time and resources
-Be able to develop, monitor and update a plan, in the light of changing circumstances
-Be able to reflect on own learning and performance, and plan its development/improvement, as a foundation for life-long learning

Underpinning learning
-Know and understand scientific principles necessary to underpin their education in electronic and electrical engineering, to enable appreciation of its scientific and engineering content, and to support their understanding of historical, current and future developments
-Know and understand the mathematical principles necessary to underpin their education in electronic and electrical engineering and to enable them to apply mathematical methods, tools and notations proficiently in the analysis and solution of engineering problems
-Be able to apply and integrate knowledge and understanding of other engineering disciplines to support study of electronic and electrical engineering

Engineering problem-solving
-Understand electronic and electrical engineering principles and be able to apply them to analyse key engineering processes
-Be able to identify, classify and describe the performance of systems and components through the use of analytical methods and modelling techniques
-Be able to apply mathematical and computer-based models to solve problems in electronic and electrical engineering, and be able to assess the limitations of particular cases
-Be able to apply quantitative methods relevant to electronic and electrical engineering, in order to solve engineering problems
-Understand and be able to apply a systems approach to electronic and electrical engineering problems

Engineering tools
-Have relevant workshop and laboratory skills
-Be able to write simple computer programs, be aware of the nature of microprocessor programming, and be aware of the nature of software design
-Be able to apply computer software packages relevant to electronic and electrical engineering, in order to solve engineering problems

Technical expertise
-Know and understand the facts, concepts, conventions, principles, mathematics and applications of the range of electronic and electrical engineering topics he/she has chosen to study
-Know the characteristics of particular materials, equipment, processes or products
-Have thorough understanding of current practice and limitations, and some appreciation of likely future developments
-Be aware of developing technologies related to electronic and electrical engineering
-Have comprehensive understanding of the scientific principles of electronic engineering and related disciplines
-Have comprehensive knowledge and understanding of mathematical and computer models relevant to electronic and electrical engineering, and an appreciation of their limitations
-Know and understand, at Master's level, the facts, concepts, conventions, principles, mathematics and applications of a range of engineering topics that he/she has chosen to study
-Have extensive knowledge of a wide range of engineering materials and components
-Understand concepts from a range of areas including some from outside engineering, and be able to apply them effectively in engineering projects

Societal and environmental context
-Understand the requirement for engineering activities to promote sustainable development
-Relevant part of: Be aware of the framework of relevant legal requirements governing engineering activities, including personnel, health, safety and risk (including environmental risk issues
-Understand the need for a high level of professional and ethical conduct in engineering

Employment context
-Know and understand the commercial and economic context of electronic and electrical engineering processes
-Understand the contexts in which engineering knowledge can be applied (e.g. operations and management, technology development, etc.)
-Be aware of the nature of intellectual property
-Understand appropriate codes of practice and industry standards
-Be aware of quality issues
-Be able to apply engineering techniques taking account of a range of commercial and industrial constraints
-Understand the basics of financial accounting procedures relevant to engineering project work
-Be able to make general evaluations of commercial risks through some understanding of the basis of such risks
-Be aware of the framework of relevant legal requirements governing engineering activities, including personnel, health, safety and risk (including environmental risk) issues

Research and development
-Understand the use of technical literature and other information sources
-Be aware of the need, in appropriate cases, for experimentation during scientific investigations and during engineering development
-Be able to use fundamental knowledge to investigate new and emerging technologies
-Be able to extract data pertinent to an unfamiliar problem, and employ this data in solving the problem, using computer-based engineering tools when appropriate
-Be able to work with technical uncertainty

Design
-Understand the nature of the engineering design process
-Investigate and define a problem and identify constraints, including environmental and sustainability limitations, and health and safety and risk assessment issues
-Understand customer and user needs and the importance of considerations such as aesthetics
-Identify and manage cost drivers
-Use creativity to establish innovative solutions
-Ensure fitness for purpose and all aspects of the problem including production, operation, maintenance and disposal
-Manage the design process and evaluate outcomes
-Have wide knowledge and comprehensive understanding of design processes and methodologies and be able to apply and adapt them in unfamiliar situations
-Be able to generate an innovative design for products, systems, components or processes, to fulfil new needs

Project management
-Be able to work as a member of a team
-Be able to exercise leadership in a team
-Be able to work in a multidisciplinary environment
-Know about management techniques that may be used to achieve engineering objectives within the commercial and economic context of engineering processes
-Have extensive knowledge and understanding of management and business practices, and their limitations, and how these may be applied appropriately

FACILITIES, EQUIPMENT AND SUPPORT

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 Faculty’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.

Specialist experimental and research facilities, for computationally demanding projects or those requiring specialist equipment, are provided by the Centre for Vision, Speech and Signal Processing (CVSSP).

CAREER PROSPECTS

Computer vision specialists are be valuable in all industries that require intelligent processing and interpretation of image and video. This includes industries in directly related fields such as:
-Multimedia indexing and retrieval (Google, Microsoft, Apple)
-Motion capture (Foundry)
-Media production (BBC, Foundry)
-Medical Imaging (Siemens)
-Security and Defence (BAE, EADS, Qinetiq)
-Robotics (SSTL)

Studying for Msc degree in Computer Vision offers variety, challenge and stimulation. It is not just the introduction to a rewarding career, but also offers an intellectually demanding and exciting opportunity to break through boundaries in research.

Many of the most remarkable advancements in the past 60 years have only been possible through the curiosity and ingenuity of engineers. Our graduates have a consistently strong record of gaining employment with leading companies.

Employers value the skills and experience that enable our graduates to make a positive contribution in their jobs from day one.

Our graduates are employed by companies across the electronics, information technology and communications industries. Recent employers include:
-BAE Systems
-BT
-Philips
-Hewlett Packard
-Logica
-Lucent Technologies
-BBC
-Motorola
-NEC Technologies
-Nokia
-Nortel Networks
-Red Hat

INDUSTRIAL COLLABORATIONS

We draw on our industry experience to inform and enrich our teaching, bringing theoretical subjects to life. Our industrial collaborations include:
-Research and technology transfer projects with industrial partners such as the BBC, Foundry, LionHead and BAE
-A number of our academics offer MSc projects in collaboration with our industrial partners

RESEARCH PERSPECTIVES

This course gives an excellent preparation for continuing onto PhD studies in computer vision related domains.

GLOBAL OPPORTUNITIES

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.

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Overview. The Master of Medical Physics is the entry level qualification that medical physicists have as clinical physical scientists. Read more
Overview
The Master of Medical Physics is the entry level qualification that medical physicists have as clinical physical scientists. It provides you with the tools to apply your knowledge and training to many different areas of medicine including the treatment of cancer, diagnostic imaging, physiological monitoring and medical electronics.

Our postgraduate medical physics program is designed to meet the growing global demand for graduate physical scientists with the specialised knowledge, skills and expertise to work within a clinical setting in the highly scientific and technical environment of medical physics. The University of Sydney Medical Physics Program offers you a wide variety of coursework units of study in radiation physics, nuclear physics, radiation dosimetry, anatomy and biology, nuclear medicine, radiotherapy physics, medical imaging physics, image processing, radiation biology, health physics and research methodology.

Sydney advantage
This program is offered through the School of Physics, which has access to world-class teaching and research facilities and provides highly experienced teaching and research staff in this discipline area through the Institute of Medical Physics and affiliated teaching hospitals and research institutes.

Program expectations
You will learn the latest knowledge and techniques enabling you to find employment in the areas of medical physics applied to the treatment of cancer, medical imaging, physiological monitoring and medical electronics.

To ask a question about this course, visit http://sydney.edu.au/internationaloffice/

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The M.Sc. in Medical Physics is a full time course which aims to equip you for a career as a scientist in medicine. You will be given the basic knowledge of the subject area and some limited training. Read more
The M.Sc. in Medical Physics is a full time course which aims to equip you for a career as a scientist in medicine. You will be given the basic knowledge of the subject area and some limited training. The course consists of an intense program of lectures and workshops, followed by a short project and dissertation. Extensive use is made of the electronic learning environment "Blackboard" as used by NUI Galway. The course has been accredited by the Institute of Physics and Engineering in Medicine (UK).

Syllabus Outline. (with ECTS weighting)
Human Gross Anatomy (5 ECTS)
The cell, basic tissues, nervous system, nerves and muscle, bone and cartilage, blood, cardiovascular system, respiratory system, gastrointestinal tract, nutrition, genital system, urinary system, eye and vision, ear, hearing and balance, upper limb – hand, lower limb – foot, back and vertebral column, embryology, teratology, anthropometrics; static and dynamic anthropometrics data, anthropometric dimensions, clearance and reach and range of movement, method of limits, mathematics modelling.

Human Body Function (5 ECTS)
Biological Molecules and their functions. Body composition. Cell physiology. Cell membranes and membrane transport. Cell electrical potentials. Nerve function – nerve conduction, nerve synapses. Skeletal muscle function – neuromuscular junction, muscle excitation, muscle contraction, energy considerations. Blood and blood cells – blood groups, blood clotting. Immune system. Autonomous nervous system. Cardiovascular system – electrical and mechanical activity of the heart. – the peripheral circulation. Respiratory system- how the lungs work. Renal system – how the kidneys work. Digestive system. Endocrine system – how hormones work. Central nervous system and brain function.

Occupational Hygiene (5 ECTS)
Historical development of Occupational Hygiene, Safety and Health at Work Act. Hazards to Health, Surveys, Noise and Vibrations, Ionizing radiations, Non-Ionizing Radiations, Thermal Environments, Chemical hazards, Airborne Monitoring, Control of Contaminants, Ventilation, Management of Occupational Hygiene.

Medical Informatics (5 ECTS)
Bio statistics, Distributions, Hypothesis testing. Chi-square, Mann-Whitney, T-tests, ANOVA, regression. Critical Appraisal of Literature, screening and audit. Patient and Medical records, Coding, Hospital Information Systems, Decision support systems. Ethical consideration in Research.
Practicals: SPSS. Appraisal exercises.

Clinical Instrumentation (6 ECTS)
Biofluid Mechanics: Theory: Pressures in the Body, Fluid Dynamics, Viscous Flow, Elastic Walls, Instrumentation Examples: Respiratory Function Testing, Pressure Measurements, Blood Flow measurements. Physics of the Senses: Theory: Cutaneous and Chemical sensors, Audition, Vision, Psychophysics; Instrumentation Examples: Evoked responses, Audiology, Ophthalmology instrumentation, Physiological Signals: Theory Electrodes, Bioelectric Amplifiers, Transducers, Electrophysiology Instrumentation.

Medical Imaging (10 ECTS)
Theory of Image Formation including Fourier Transforms and Reconstruction from Projections (radon transform). Modulation transfer Function, Detective Quantum Efficiency.
X-ray imaging: Interaction of x-rays with matter, X-ray generation, Projection images, Scatter, Digital Radiography, CT – Imaging. Fundamentals of Image Processing.
Ultrasound: Physics of Ultrasound, Image formation, Doppler scanning, hazards of Ultrasound.
Nuclear Medicine : Overview of isotopes, generation of Isotopes, Anger Cameras, SPECT Imaging, Positron Emitters and generation, PET Imaging, Clinical aspects of Planar, SPECT and PET Imaging with isotopes.
Magnetic Resonance Imaging : Magnetization, Resonance, Relaxation, Contrast in MR Imaging, Image formation, Image sequences, their appearances and clinical uses, Safety in MR.

Radiation Fundamentals (5 ECTS)
Review of Atomic and Nuclear Physics. Radiation from charged particles. X-ray production and quality. Attenuation of Photon Beams in Matter. Interaction of Photons with Matter. Interaction of Charged Particles with matter. Introduction to Monte Carlo techniques. Concept to Dosimetry. Cavity Theory. Radiation Detectors. Practical aspects of Ionization chambers

The Physics of Radiation Therapy (10 ECTS)
The interaction of single beams of X and gamma rays with a scattering medium. Treatment planning with single photon beams. Treatment planning for combinations of photon beams. Radiotherapy with particle beams: electrons, pions, neutrons, heavy charged particles. Special Techniques in Radiotherapy. Equipment for external Radiotherapy. Relative dosimetry techniques. Dosimetry using sealed sources. Brachytherapy. Dosimetry of radio-isotopes.

Workshops / Practicals
Hospital & Radiation Safety [11 ECTS]
Workshop in Risk and Safety.
Concepts of Risk and Safety. Legal Aspects. Fundamental concepts in Risk Assessment and Human Factor Engineering. Risk and Safety management of complex systems with examples from ICU and Radiotherapy. Accidents in Radiotherapy and how to avoid them. Principles of Electrical Safety, Electrical Safety Testing, Non-ionizing Radiation Safety, including UV and laser safety.
- NUIG Radiation Safety Course.
Course for Radiation Safety Officer.
- Advanced Radiation Safety
Concepts of Radiation Protection in Medical Practice, Regulations. Patient Dosimetry. Shielding design in Diagnostic Radiology, Nuclear Medicine and Radiotherapy.
- Medical Imaging Workshop
Operation of imaging systems. Calibration and Quality Assurance of General
radiography, fluoroscopy systems, ultrasound scanners, CT-scanners and MR scanners. Radiopharmacy and Gamma Cameras Quality Control.

Research Project [28 ECTS]
A limited research project will be undertaken in a medical physics area. Duration of this will be 4 months full time

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This programme provides graduates and working professionals with a broad training in signal processing and communications. Read more

Programme description

This programme provides graduates and working professionals with a broad training in signal processing and communications. It is suitable for recent graduates who wish to develop the specialist knowledge and skills relevant to this industry and is also suitable as advanced study in preparation for research work in an academic or industrial environment or in a specialist consultancy organisation.

Engineers or other professionals wishing to participate in the MSc programme may do so on a part-time basis.

Our students gain a thorough understanding of theoretical foundations as well as advanced topics at the cutting edge of research in signal processing and communications, including compressive sensing, deep neural networks, wireless communication theory, and numerical Bayesian methods.

The MSc project provides a good opportunity for students to work on state-of-the-art research problems in signal processing and communications.

Programme structure

This programme is run over 12 months, with two semesters of taught courses followed by a research project leading to a masters thesis.

Semester 1 courses
Discrete-Time Signal Analysis
Digital Communication Fundamentals
Probability, Random Variables and Estimation Theory
Statistical Signal Processing
Image Processing
Signal Processing Laboratory
Semester 2 courses
Adaptive Signal Processing
Advanced Coding Techniques
Advanced Wireless Communication
Array Processing Methods
Advanced Concepts in Signal Processing
Pre-dissertation project preparation and report

Career opportunities

With our excellent employability record and internationally respected reputation, the University of Edinburgh is a reliable choice for developing your engineering career.

This programme will appeal to graduates who wish to pursue a career in an industry such as communications, radar, medical imaging or anywhere else signal processing is applied.

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The Medical Physics and Bioengineering MRes provides structured training in this diverse and multidisciplinary field and students may subsequently progress to an MPhil/PhD as part of a Doctoral Training Programme. Read more
The Medical Physics and Bioengineering MRes provides structured training in this diverse and multidisciplinary field and students may subsequently progress to an MPhil/PhD as part of a Doctoral Training Programme.

Degree information

The programme covers all forms of ionising and non-ionising radiation commonly used in medicine and applies it to the areas of imaging and treatment. The programme involves Master's level modules chosen from a wide range offered by the department and a research project. Good performance in the MRes will lead to entry into the 2nd year of the Doctoral Training Programme where the research project is continued.

Students undertake modules to the value of 180 credits. The programme consists of four optional modules and a research project. There are no core modules for this programme.

Optional modules - students choose four optional modules from the following:
-Ionising Radiation Physics: Interactions and Dosimetry
-Medical Imaging
-Clinical Practice
-Treatment with Ionising Radiation
-Medical Electronics and Control
-Bioengineering
-Optics in Medicine
-Computing in Medicine
-Medical Devices and Applications
-Foundations and Anatomy and Scientific Computing
-Image Processing
-Computational Modelling in Biomedical Imaging
-Programming Foundations for Medical Image Analysis
-Information Processing in Medical Imaging
-Image-Directed Analysis and Therapy

Dissertation/report
All students undertake a research project.

Careers

Our graduates typically find work in academia, the NHS, and in industry.

Why study this degree at UCL?

The department is one of the largest medical physics and bioengineering departments in Europe, with links to a large number of active teaching hospitals. We have arguably the widest range of research of any similar department, and work closely with other world-leading institutions.

Students on the programme will form part of an interactive network of researchers across many disciplines and will benefit from the strengths of UCL in the healthcare field.

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The MSc in Digital Signal and Image Processing has been developed to deliver qualified engineers of the highest standard into the emerging field of digital signal and image processing who are capable of contributing significantly to this increased demand for both real-time and off-line systems operating over a range of mobile, embedded and workstation platforms. Read more
The MSc in Digital Signal and Image Processing has been developed to deliver qualified engineers of the highest standard into the emerging field of digital signal and image processing who are capable of contributing significantly to this increased demand for both real-time and off-line systems operating over a range of mobile, embedded and workstation platforms. The DSIP option of the MSc in Computational and Software Techniques in Engineering aims to develop your skill-base for the rapidly expanding engineering IT industry sector, not only in the UK but all over the world. Graduates in this option have the opportunity to pursue a wide range of careers embracing telecommunications, the automotive industry, medical imaging, software houses and industrial research where demand for skills is high.

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This course provides a thorough, methodical and wide-ranging education in digital signal and image processing. The Degree course offers both core taught modules and a substantial individual research project. Read more
This course provides a thorough, methodical and wide-ranging education in digital signal and image processing. The Degree course offers both core taught modules and a substantial individual research project.

Teaching and learning

The course contains both compulsory core taught modules and a substantial individual research project. Four taught modules are delivered in the first semester from September to January, and four taught modules are delivered in the second semester from February to June. Each taught unit is assessed by coursework or laboratory report, with written examinations in January and June.
You will conduct your dissertation project work during summer and submit your final dissertation in September.

Course unit details

Typical course units include:
-Signals and data capture engineering
-Digital image processing
-Digital Communications engineering
-Sensing and transduction
-Digital image engineering
-Tomography engineering and applications

Career opportunities

Digital signals are part of almost every aspect of 21st technology. If you take this course, you will become expert in this area and expose yourself to a world of opportunity respecting careers. You will, for example, be able to perform biomedical signal processing, audio/visual/multimedia engineering, digital waveform synthesis and medical, industrial and military image processing. You will be able to work in the fields of imaging, medical physics, aerospace, telecommunications systems development, mechatronics, robotics, remote sensing and nondestructive testing. Your skills will be highly sought after in organisations that develop systems for these and many related state-of the art disciplines.

This course will not only make you very employable; it will be a very fulfilling and enriching experience.

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Through a mix of lectures, laboratories, clinical demonstrations and hospital visits, our MSc in Medical Imaging will develop you as a professional, enhancing your ability to take on new challenges with confidence. Read more
Through a mix of lectures, laboratories, clinical demonstrations and hospital visits, our MSc in Medical Imaging will develop you as a professional, enhancing your ability to take on new challenges with confidence. This programme is run together with the Department of Physics.

PROGRAMME OVERVIEW

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.

PROGRAMME STRUCTURE

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. 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.
-Image Processing and Vision
-Professional Skills for Clinical Science and Engineering
-Radiation Biology
-Radiation Physics
-AI and AI Programming
-Computer Vision and Pattern Recognition
-Diagnostic Apps of Ionising Radiation
-Non-Ionising Radiation Imaging
-Engineering Professional Studies 1
-Engineering Professional Studies 2
-Extended Project

FACILITIES, EQUIPMENT AND SUPPORT

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.

EDUCATIONAL AIMS OF THE PROGRAMME

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:
-Attract well-qualified entrants, with a background in Electronic Engineering, Physical Sciences, Mathematics, Computing & Communications, from the UK, Europe and overseas
-Provide participants with advanced knowledge, practical skills and understanding applicable to the MSc degree
-Develop participants' understanding of the underlying science, engineering, and technology, and enhance their ability to relate this to industrial practice
-Develop participants' critical and analytical powers so that they can effectively plan and execute individual research/design/development projects
-Provide a high level of flexibility in programme pattern and exit point
-Provide students with an extensive choice of taught modules, in subjects for which the Department has an international and UK research reputation

PROGRAMME LEARNING OUTCOMES

The programme provides opportunities for students to develop and demonstrate knowledge and understanding, skills, qualities and other attributes in the following areas:

General transferable skills
-Be able to use computers and basic IT tools effectively
-Information retrieval. Be able to retrieve information from written and electronic sources
-Be able to apply critical but constructive thinking to received information
-Be able to study and learn effectively
-Be able to communicate effectively in writing and by oral presentations
-Be able to present quantitative data effectively, using appropriate methods
-Be able to manage own time and resources
-Be able to develop, monitor and update a plan, in the light of changing circumstances
-Be able to reflect on own learning and performance, and plan its development/improvement, as a foundation for life-long learning

Underpinning learning
-Know and understand scientific principles necessary to underpin their education in electronic and electrical engineering, to enable appreciation of its scientific and engineering content, and to support their understanding of historical, current and future developments
-Know and understand the mathematical principles necessary to underpin their education in electronic and electrical engineering and to enable them to apply mathematical methods, tools and notations proficiently in the analysis and solution of engineering problems
-Be able to apply and integrate knowledge and understanding of other engineering disciplines to support study of electronic and electrical engineering

Engineering problem-solving
-Understand electronic and electrical engineering principles and be able to apply them to analyse key engineering processes
-Be able to identify, classify and describe the performance of systems and components through the use of analytical methods and modelling techniques
-Be able to apply mathematical and computer-based models to solve problems in electronic and electrical engineering, and be able to assess the limitations of particular cases
-Be able to apply quantitative methods relevant to electronic and electrical engineering, in order to solve engineering problems
-Understand and be able to apply a systems approach to electronic and electrical engineering problems

Engineering tools
-Have relevant workshop and laboratory skills
-Be able to write simple computer programs, be aware of the nature of microprocessor programming, and be aware of the nature of software design
-Be able to apply computer software packages relevant to electronic and electrical engineering, in order to solve engineering problems

Technical expertise
-Know and understand the facts, concepts, conventions, principles, mathematics and applications of the range of electronic and electrical engineering topics he/she has chosen to study
-Know the characteristics of particular materials, equipment, processes or products
-Have thorough understanding of current practice and limitations, and some appreciation of likely future developments
-Be aware of developing technologies related to electronic and electrical engineering
-Have comprehensive understanding of the scientific principles of electronic engineering and related disciplines
-Have comprehensive knowledge and understanding of mathematical and computer models relevant to electronic and electrical engineering, and an appreciation of their limitations
-Know and understand, at Master's level, the facts, concepts, conventions, principles, mathematics and applications of a range of engineering topics that he/she has chosen to study
-Have extensive knowledge of a wide range of engineering materials and components
-Understand concepts from a range of areas including some from outside engineering, and be able to apply them effectively in engineering projects

Societal and environmental content
-Understand the requirement for engineering activities to promote sustainable development
-Be aware of the framework of relevant legal requirements governing engineering activities, including personnel, health, safety and risk (including environmental risk issues
-Understand the need for a high level of professional and ethical conduct in engineering

Employment context
-Know and understand the commercial and economic context of electronic and electrical engineering processes
-Understand the contexts in which engineering knowledge can be applied (e.g. operations and management, technology development, etc.)
-Understand appropriate codes of practice and industry standards
-Be aware of quality issues
-Be able to apply engineering techniques taking account of a range of commercial and industrial constraints
-Understand the basics of financial accounting procedures relevant to engineering project work
-Be able to make general evaluations of commercial risks through some understanding of the basis of such risks
-Be aware of the framework of relevant legal requirements governing engineering activities, including personnel, health, safety and risk (including environmental risk) issues

Research and development
-Understand the use of technical literature and other information sources
-Be aware of the need, in appropriate cases, for experimentation during scientific investigations and during engineering development
-Be able to use fundamental knowledge to investigate new and emerging technologies
-Be able to extract data pertinent to an unfamiliar problem, and employ this data in solving the problem, using computer-based engineering tools when appropriate
-Be able to work with technical uncertainty

Design
-Understand the nature of the engineering design process
-Investigate and define a problem and identify constraints, including environmental and sustainability limitations, and health and safety and risk assessment issues
-Understand customer and user needs and the importance of considerations such as aesthetics
-Identify and manage cost drivers
-Use creativity to establish innovative solutions
-Ensure fitness for purpose and all aspects of the problem including production, operation, maintenance and disposal
-Manage the design process and evaluate outcomes
-Have wide knowledge and comprehensive understanding of design processes and methodologies and be able to apply and adapt them in unfamiliar situations
-Be able to generate an innovative design for products, systems, components or processes, to fulfil new needs

Project management
-Be able to work as a member of a team
-Be able to exercise leadership in a team
-Be able to work in a multidisciplinary environment
-Know about management techniques that may be used to achieve engineering objectives within the commercial and economic context of engineering processes
-Have extensive knowledge and understanding of management and business practices, and their limitations, and how these may be applied appropriately

GLOBAL OPPORTUNITIES

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.

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Signal processing is recognised as a core technology in rapidly growing areas such as sensor networks, medical devices and renewable energy, audio, image and video systems. Read more

Why this course?

Signal processing is recognised as a core technology in rapidly growing areas such as sensor networks, medical devices and renewable energy, audio, image and video systems. It’s the underpinning technology of all communication including the internet, wireless and satellite.

We’ve been carrying out research and development in signal processing for more than 30 years. Many of today’s industry leaders are alumni of the University and this industry awareness and experience underpins this specialised degree.

This MSc aims to address the growing skills shortage in industry of engineers who have an understanding of the complete signal processing design cycle. It’s also essential preparation if you’re considering advanced research in applied signal processing.

See the website https://www.strath.ac.uk/courses/postgraduatetaught/signalprocessing/

What you’ll study

There are two semesters of compulsory and optional classes, followed by a three-month practical research project in a specialist area. There’s the opportunity to carry this out through the department's competitive MSc industrial internships.

The internships are offered in collaboration with selected department industry partners eg ScottishPower, SmarterGridSolutions, SSE. You'll address real-world engineering challenges facing the partner, with site visits, access and provision of relevant technical data and/or facilities provided, along with an industry mentor and academic supervisor.

Facilities

You'll have exclusive access to our extensive computing network and purpose built teaching spaces such as our Hyperspectral Imaging Centre and the DG Smith Radio Frequency laboratory, equipped with the latest technologies.

Accreditation

The course is fully accredited by the professional body, the Institution of Engineering and Technology (IET). This means that you'll meet the educational requirements to become a Chartered Engineer – a must for your future engineering career.

Pre-Masters preparation course

The Pre-Masters Programme is a preparation course for international students (non EU/UK) who do not meet the entry requirements for a Masters degree at University of Strathclyde. The Pre-Masters programme provides progression to a number of degree options.

To find out more about the courses and opportunities on offer visit isc.strath.ac.uk or call today on +44 (0) 1273 339333 and discuss your education future. You can also complete the online application form. To ask a question please fill in the enquiry form and talk to one of our multi-lingual Student Enrolment Advisers today.

Learning & teaching

We use a blend of teaching and learning methods including interactive lectures, problem-solving tutorials and practical project-based laboratories. Our technical and experimental officers are available to support and guide you on individual subject material.

Each module comprises approximately five hours of direct teaching per week. To enhance your understanding of the technical and theoretical topics covered in these, you're expected to undertake a further five to six hours of self-study, using our web-based virtual learning environment (MyPlace), research journals and library facilities.

The teaching and learning methods used ensure you'll develop not only technical engineering expertise but also communications, project management and leadership skills.

- Industry engagement
Interaction with industry is provided through our internships, teaching seminars and networking events. The department delivers monthly seminars to support students’ learning and career development. Xilinx, Texas Instruments, MathWorks, and Agilent are just a few examples of the industry partners you can engage with during your course.

Assessment

A variety of assessment techniques are used throughout the course. You'll complete at least six modules. Each module has a combination of written assignments, individual and group reports, oral presentations, practical lab work and, where appropriate, an end-of-term exam.

Assessment of the summer research project/internship consists of four elements, with individual criteria:
1. Interim report (10%, 1,500 to 3,000 words) – the purpose of this report is to provide a mechanism for supervisors to provide valuable feedback on the project’s objectives and direction.

2. Poster Presentation (15%) – a vital skill of an engineer is the ability to describe their work to others and respond to requests for information. The poster presentation is designed to give you an opportunity to practise that.

3. Final report (55%) – this assesses the communication of project objectives and context, accuracy and relevant of background material, description of practical work and results, depth and soundness of discussion and conclusions, level of engineering achievement and the quality of the report’s presentation.

4. Conduct (20%) - independent study, project and time management are key features of university learning. The level of your initiative & independent thinking and technical understanding are assessed through project meetings with your supervisor and your written logbooks.

Careers

With Signal Processing being a core technology in high-growth areas such as sensor networks, medical devices, renewable energy and communications, this course enables you to capitalise on job opportunities across all of these sectors, as well as in electronics design, IT, banking, and oil and gas.

Almost all of our graduates secure jobs by the time they have completed their course. They've taken up well-paid professional and technical occupations with multinationals such as Google, Microsoft, Texas Instruments, Motorola Mobility, Intel, as well as Wolfson Microelectronics, Agilent, Freescale and Thales in the vibrant national UK arena.

Find information on Scholarships here http://www.strath.ac.uk/engineering/electronicelectricalengineering/ourscholarships/.

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This programme is structured around topics in systems and signal processing, with specialisms in control and systems theory, image processing and machine learning. Read more

Course Summary

This programme is structured around topics in systems and signal processing, with specialisms in control and systems theory, image processing and machine learning. Skills developed are sought after by industry (biotech, financial services, systems engineering, medical imaging, etc) and the academic research community. The modules have a high mathematical content and much of the material is computationally based, developing strong transferable skills in algorithmic development and programming.

Modules

Semester one: Signal Processing; Control System Design; Machine Learning; Computer Vision

Semester two: Advanced Systems and Signal Processing; Digital Control System Design; Applied Control Systems; Biological Inspired Robotics; Advanced Computer Vision; Image Processing; Advanced Machine Learning; Computational Finance; Computational Biology; Biometrics

Visit our website for further information...



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See the department website - http://www.cis.rit.edu/graduate-programs/master-science. The master of science program in imaging science prepares students for positions in research in the imaging industry or in the application of various imaging modalities to problems in engineering and science. Read more
See the department website - http://www.cis.rit.edu/graduate-programs/master-science

The master of science program in imaging science prepares students for positions in research in the imaging industry or in the application of various imaging modalities to problems in engineering and science. Formal course work includes consideration of the physical properties of radiation-sensitive materials and processes, the applications of physical and geometrical optics to electro-optical systems, the mathematical evaluation of image forming systems, digital image processing, and the statistical characterization of noise and system performance. Technical electives may be selected from courses offered in imaging science, color science, engineering, computer science, science, and mathematics. Both thesis and project options are available. In general, full-time students are required to pursue the thesis option, with the project option targeted to part-time and online students who can demonstrate that they have sufficient practical experience through their professional activities.

Faculty within the Center for Imaging Science supervise thesis research in areas of the physical properties of radiation-sensitive materials and processes, digital image processing, remote sensing, nanoimaging, electro-optical instrumentation, vision, medical imaging, color imaging systems, and astronomical imaging. Interdisciplinary efforts are possible with other colleges across the university.

The program can be completed on a full- or a part-time basis. Some courses are available online, specifically in the areas of color science, remote sensing, medical imaging, and digital image processing.

Plan of study

All students must earn 30 credit hours as a graduate student. The curriculum is a combination of required core courses in imaging science, elective courses appropriate for the candidate’s background and interests, and either a research thesis or graduate paper/project. Students must enroll in either the research thesis or graduate paper/project option at the beginning of their studies.

Core courses

Students are required to complete the following core courses: Fourier Methods for Imaging (IMGS-616), Image Processing and Computer Vision (IMGS-682), Optics for Imaging (IMGS-633), and either Radiometry (IMGS-619) or The Human Visual System (IMGS-620).

Speciality track courses

Students choose two courses from a variety of tracks such as: digital image processing, medical imaging, electro-optical imaging systems, remote sensing, color imaging, optics, hard copy materials and processes, and nanoimaging. Tracks may be created for students interested in pursuing additional fields of study.

Research thesis option

The research thesis is based on experimental evidence obtained by the student in an appropriate field, as arranged between the student and their adviser. The minimum number of thesis credits required is four and may be fulfilled by experiments in the university’s laboratories. In some cases, the requirement may be fulfilled by work done in other laboratories or the student's place of employment, under the following conditions:

1. The results must be fully publishable.

2. The student’s adviser must be approved by the graduate program coordinator.

3. The thesis must be based on independent, original work, as it would be if the work were done in the university’s laboratories.

A student’s thesis committee is composed of a minimum of three people: the student’s adviser and two additional members who hold at least a master's dgeree in a field relevant to the student’s research. Two committee members must be from the graduate faculty of the center.

Graduate paper/project option

Students with demonstrated practical or research experience, approved by the graduate program coordinator, may choose the graduate project option (3 credit hours). This option takes the form of a systems project course. The graduate paper is normally performed during the final semester of study. Both part- and full-time students may choose this option, with the approval of the graduate program coordinator.

Admission requirements

To be considered for admission to the MS in imaging science, candidates must fulfill the following requirements:

- Hold a baccalaureate degree from an accredited institution (undergraduate studies should include the following: mathematics, through calculus and including differential equations; and a full year of calculus-based physics, including modern physics. It is assumed that students can write a common computer program),

- Submit a one- to two-page statement of educational objectives,

- Submit official transcripts (in English) of all previously completed undergraduate or graduate course work,

- Submit letters of recommendation from individuals familiar with the applicant’s academic or research capabilities,

- Submit scores from the Graduate Record Exam (GRE) (requirement may be waived for those not seeking funding from the Center for Imaging Science), and

- Complete a graduate application.

- International applicants whose native language is not English must submit scores from the Test of English as a Foreign Language. Minimum scores of 600 (paper-based) or 100 (Internet-based) are required. Students may also submit scores from the International English Language Testing System. The minimum IELTS score is 7.0. International students who are interested in applying for a teaching or research assistantship are advised to obtain as high a TOEFL or IELTS score as possible. These applicants also are encouraged to take the Test of Spoken English in order to be considered for financial assistance.

Applicants seeking financial assistance from the center must have all application documents submitted to the Office of Graduate Enrollment Services by January 15 for the next academic year.

Additional information

- Bridge courses

Applicants who lack adequate preparation may be required to complete bridge courses in mathematics or physics before matriculating with graduate status.

- Maximum time limit

University policy requires that graduate programs be completed within seven years of the student's initial registration for courses in the program. Bridge courses are excluded.

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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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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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Demand is growing for high value data specialists across the sciences, medicine, arts and humanities. The aim of this unique, modular, online distance learning programme is to enhance existing career paths with an additional dimension in data science. Read more

Programme description

Demand is growing for high value data specialists across the sciences, medicine, arts and humanities. The aim of this unique, modular, online distance learning programme is to enhance existing career paths with an additional dimension in data science.

The programme is designed to fully equip tomorrow’s data professionals, offering different entry points into the world of data science – across the sciences, medicine, arts and humanities.

Students will develop a strong knowledge foundation of specific disciplines as well as direction in technology, concentrating on the practical application of data research in the real world.

You can study to an MSc, Postgraduate Diploma, Postgraduate Certificate or Postgraduate Professional Development level.

Online learning

Our online learning technology is fully interactive, award-winning and enables you to communicate with our highly qualified teaching staff from the comfort of your own home or workplace.

Our online students not only have access to the University of Edinburgh’s excellent resources, but also become part of a supportive online community, bringing together students and tutors from around the world.

Programme structure

You can study to an MSc, Postgraduate Diploma, Postgraduate Certificate or Postgraduate Professional Development level.

For the MSc programme, students must successfully complete a total of 180 credits: Practical Introduction to Data Science (20 credits), the Dissertation Project (60 credits) plus 100 credits from the list of courses below.

For the MSc with specialism in Medical Informatics, students must successfully complete a total of 180 credits: Medical Informatics (10 credits), Research and Evaluation in eHealth (10 credits), the Dissertation Project (60 credits) plus 100 credits from the list of courses below. Students wishing to study the MSc with specialism in Medical Informatics should apply for the standard MSc in Data Science, Technology and Innovation and contact the Programme Administrator to discuss the specialism.

For the Postgraduate Diploma (PG Dip), students must successfully complete a total of 120 credits: Practical Introduction to Data Science (20 credits) plus 100 credits from the list of courses below.

For the Postgraduate Certificate (PgCert), students must successfully complete a total of 60 credits: Practical Introduction to Data Science (20 credits) plus 40 credits from the list of courses below.

For the Postgraduate Professional Development (PPD), students may take a maximum of 50 credits from the list of courses below. These credits will be recognised in their own right for postgraduate level credits or may be put towards gaining a higher award such as a PgCert.

Option courses

Some option courses may be compulsory for a specific programme; please refer to the information above.

Advanced Vision (10 credits)
Engaging with Digital Research (10 credits)
Ethics and Governance of eHealth (10 credits)
Introduction to Clinical Trials (10 credits)
Introduction to Health Informatics 1 (10 credits)
Introduction to Health Informatics 2 (10 credits)
Introduction to Vision and Robotics (10 credits)
Machine Learning (10 credits)
Managing Digital Influence (10 credits)
Medical Informatics (10 credits)
Neuroimaging: Common Image Processing Techniques 1 (20 credits)
Neuroimaging: Common Image Processing Techniques 2 (10 credits)
Practical Introduction to Data Science (20 credits)
Practical Introduction to High Performance Computing (20 credits)
Public Health Informatics (10 credits)
Research and Evaluation in eHealth (10 credits) (restricted to the MSc and MSc with Medical Informatics programmes)
Social Shaping of Digital Research (10 credits)
Technologies of Civic Participation (10 credits)
Telemedicine and Telehealth (10 credits)
The Use and Evolution of Digital Data Analysis and Collection Tools (10 credits)
Understanding Data Visualisation (10 credits)
User Centred Design in eHealth (10 credits)
Dissertation project – all Masters

(We recommend you take Introduction to Vision and Robotics before or simultaneously taking Advanced Vision, or have some previous experience with image processing.)

Learning outcomes

The modular course structure offers broad engagement at different career stages. Individual courses provide an understanding of modern data-intensive approaches while the programme provides the knowledge base to develop a career that majors in data science in an applied domain.

Career opportunities

This programme is intended for professionals wishing to develop an awareness of applications and implications of data intensive systems. Our aim is to enhance existing career paths with an additional dimension in data science, through new technological skills and/or better ability to engage with data in target domains of application.

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