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Masters Degrees (Electrical Machine)

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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.

About this degree

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 two core modules (30 credits), four to six optional modules (60 to 90 credits), up to two elective modules (up to 30 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 (15 credits)
  • Statistical Modelling and Data Analysis (15 credits)

Optional modules

Students must choose 15 credits from Group One Options. Of the remaining credits, students must choose a minimum of 30 and a maximum of 60 from Group Two, 15 credits from Group Three and a maximum of 30 credits from Electives.

Group One Options (15 credits)

  • Graphical Models (15 credits)
  • Probabilistic and Unsupervised Learning (15 credits)

Group Two Options (30 to 60 credits)

  • Advanced Deep Learning and Reinforcement Learning (15 credits)
  • Advanced Topics in Machine Learning (15 credits)
  • Applied Machine Learning (15 credits)
  • Approximate Inference and Learning in Probabilistic Models (15 credits)
  • Information Retrieval and Data Mining (15 credits)
  • Introduction to Deep Learning (15 credits)
  • Machine Vision (15 credits)
  • Statistical Natural Language Processing (15 credits)

Group Three Options (15 credits)

  • Applied Bayesian Methods (15 credits)
  • Statistical Design of Investigations (15 credits)
  • Statistical Inference (15 credits)

Please note: the availability and delivery of optional modules may vary, depending on your selection.

A list of acceptable elective modules is available on the Departmental page.

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.

Further information on modules and degree structure is available on the department website: Computational Statistics and Machine Learning MSc

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.

Recent career destinations for this degree

  • Data Scientist, Interpretive
  • Software Engineer, Google
  • Data Scientist, YouGov
  • Research Engineer, DeepMind
  • PhD in Computer Science, UCL

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.

Careers data is taken from the ‘Destinations of Leavers from Higher Education’ survey undertaken by HESA looking at the destinations of UK and EU students in the 2013–2015 graduating cohorts six months after graduation.

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 the 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.

Research Excellence Framework (REF)

The Research Excellence Framework, or REF, is the system for assessing the quality of research in UK higher education institutions. The 2014 REF was carried out by the UK's higher education funding bodies, and the results used to allocate research funding from 2015/16.

The following REF score was awarded to the department: Computer Science

96% rated 4* (‘world-leading’) or 3* (‘internationally excellent’)

Learn more about the scope of UCL's research, and browse case studies, on our Research Impact website.



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Do you want to be able to help design the next generation of renewable energy systems, clean cars and aircraft? Do you want to be able to invent the electrical systems for future factories and robots?. Read more
Do you want to be able to help design the next generation of renewable energy systems, clean cars and aircraft? Do you want to be able to invent the electrical systems for future factories and robots?

The Power Electronics, Machines and Drives (PEMD) is a 1 year degree course that provides its students with the knowledge to design, construct and analyse integrated networks of power electronic converters, electrical machines, actuators, energy storage devices, and control systems. As a result of recent technical advances, PEMD technology is becoming commonplace and can be found for example in more-electric aircraft and ships, electric vehicles, railway systems, renewable power generation, active management of power distribution systems, automation systems for factories and industrial processes. The adoption of PEMD technology is being driven by the need to increase energy efficiency, and controllability, whilst reducing system weight and maintenance costs.

This MSc course has been designed to equip electrical engineers with the knowledge and skills that are required to design modern PEMD systems, it includes the fundamentals of electrical machine and power electronics design, system integration, control, energy management and protection. The teaching team of eight academic staff belong to the Power Conversion Group and are all actively involved in researching new aspects of machines, drives, power electronics and electrical systems, particularly for applications in transport and sustainable electricity supply. The Group's research activities and industrial links inform the course content and enrich the student experience.

Aims

-To enable you to gain experience in the design and analysis of systems in electrical engineering, for example renewable energy, more-electric aircraft, vehicles, and next-generation electric power transmission
-To enable you to critically evaluate electrical machine and converter technology applied in manufacturing, power systems and transport industries
-To employ recent developments in these research areas and to prepare students who wish to continue on to research studies
-To develop your ability to integrate strands of machines, power electronics, drives and their control

The MSc course begins with an introduction to the fundamentals of converters, machines, actuators and relevant control systems. The course will give you a high level of exposure to system integration and is illustrated by a broad range of high-technology activities related to industrial and other systems.

The next five course units give specialist tuition on advanced topics including machine design, systems analysis, converter circuits and applications. In addition to lectures, tutorials, design exercises and enquiry-based learning, you will attend industrial seminars and practical laboratories which employ mainly industrial equipment. The course will include a `mechatronic' emphasis in examining how system blocks interact and ensuring that electrical and mechanical systems work together.

The summer is spent on this individual dissertation project, which is strongly supported by the Power Conversion Research Group's research base (including the Rolls-Royce University Technology Centre) and extensive industrial contacts. Cutting-edge research areas include versatile power and conversion systems for a variety of applications, including more-electric aircraft and ships, electric and hybrid vehicles, automation systems and autonomous/micro-grid power systems.

Career opportunities

Graduates of the course will have acquired in-depth education in modern design, broad exposure to the expanding range of applications, hands-on experience and integration into state-of-the-art systems. These comprise the special knowledge and skills needed for a professional career in energy conversion systems, an area in which engineers are in demand for key power electronic/drives/automation industries.

Industry's competitive edge relies on high-technology drives and in the integration of systems to provide superior overall performance. Applications include the `more electric aircraft', electric transport and high-reliability systems.

Our students have been employed by companies such as:
-ABB
-BAE Systems
-Cummings Turbo Technologies
-GE Energy
-National Instruments
-Rolls-Royce
-Siemens

Opportunities also exist for further study to doctoral level (PhD) in the Power Conversion Group's recently re-equipped and expanding research laboratories.

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Our Masters in Electrical and Electronic Engineering is an advanced course designed for engineering graduates to enhance their skills in this area of high technology. Read more
Our Masters in Electrical and Electronic Engineering is an advanced course designed for engineering graduates to enhance their skills in this area of high technology. The ever increasing pace of developments in all areas of electrical and electronic engineering, (and in particular in the systems that are related to energy and the environment), requires engineers with a thorough understanding of operation principles and design methods for various modern electrical and electronic systems. As a graduate you'll be able to not only respond to the latest changes but also to look ahead and help in shaping future developments.

The unique features of this course are that the traditional electrical and electronic engineering subjects are supported by the more modern topics of computer control and machine learning techniques, which are at the forefront of modern electrical and electronic systems in the industry today. This course offers an integrated systems approach to engineering, incorporating modules in advanced power electronics and renewable energy systems, advanced instrumentation and control with signal processing, real-time systems and machine learning techniques.

There is an increasing demand for skilled engineers who are able to design and maintain electrical and electronic systems that are at the forefront of current technologies. These positions cover many industries, hence graduates from this course can expect significantly enhanced job prospects in electrical, electronic as well as systems engineering.

Modules

Digital signal processing
Pattern recognition and machine learning
Advanced Instrumentation and Design
Advanced power electronics and renewable energy systems
Technology evaluation and commercialization
Technical, research and professional skills
MSc engineering project

Professional links

The School has a strong culture of research and extensive research links with industry through consultancy works and Knowledge Transfer Partnerships (KTPs). Teaching content on our courses is closely related to the latest research work.

This course is accredited by the IET as meeting the further learning requirements for CEng registration. The IET is one of the world’s largest engineering institutions with over 167,000 members in 127 countries.

Employability

The acquired skills in computer control and AI techniques offer additional scope for jobs in the design of decision support systems that cross traditional boundaries between engineering and other disciplines. (i.e. medical, finance). Successful graduates will enjoy exciting career opportunities from a wide range of industries, such as electrical energy supply and control, electronics and instrumentation products and services, intelligent systems and automation to include: automotive, aerospace, electrical and electronic consumer products, telecommunications. The students can also pursue PhD studies after completing the course.

Engineering management skills

Engineering employers have expressed their need for engineers with a solid grasp of the business requirements that underpin real engineering projects. Our course incorporates a management-related module focused on entrepreneurship and project management. This management module develops our graduates' commercial awareness and ensures that they have the skill-set valued by industry employers.

LSBU Employability Services

LSBU is committed to supporting you develop your employability and succeed in getting a job after you have graduated. Your qualification will certainly help, but in a competitive market you also need to work on your employability, and on your career search. Our Employability Service will support you in developing your skills, finding a job, interview techniques, work experience or an internship, and will help you assess what you need to do to get the job you want at the end of your course. LSBU offers a comprehensive Employability Service, with a range of initiatives to complement your studies, including:

• Direct engagement from employers who come in to interview and talk to students
• Job Shop and on-campus recruitment agencies to help your job search
• Mentoring and work shadowing schemes.

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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.

About this degree

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 one core module (15 credits), five to seven optional modules (75 to 105 credits), up to two modules (30 credits) from electives, and a research project (60 credits).

Core modules

  • Supervised Learning (15 credits)

Optional modules

Students must choose 15 credits from Option Group One and a minimum of 60 credits from Option Group Two. Students must choose a further 30 credits from either Option Group Two or approved electives.

Option Group One (choose 15 credits)

  • Graphical Models (15 credits)
  • Probabilistic and Unsupervised Learning (15 credits)

Option Group Two (choose 60 to 90 credits)

  • Advanced Deep Learning and Reinforcement Learning (15 credits)
  • Advanced Topics in Machine Learning (15 credits)
  • Affective Computing and Human-Robot Interaction (15 credits)
  • Applied Machine Learning (15 credits)
  • Approximate Inference and Learning in Probabilistic Models (15 credits)
  • Bioinformatics (15 credits)
  • Information Retrieval and Data Mining (15 credits)
  • Introduction to Deep Learning (15 credits)
  • Machine Vision (15 credits)
  • Programming and Mathematical Methods for Machine Learning (15 credits)
  • Statistical Natural Language Programming (15 credits)

Please note: the availability and delivery of optional modules may vary, depending on your selection.

Students may select up to 30 credits from elective modules

A list of acceptable elective modules is available on the departmental website.

Dissertation/report

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

Further information on modules and degree structure is available on the department website: Machine Learning MSc

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

Recent career destinations for this degree

  • Computer Vision Engineer, ZVR
  • Data Analyst / Data Scientist, Deloitte Data Analytics Group
  • Programmatic Yield Manager and Data Analyst, eBay
  • Data Scientist, dunnhumby
  • PhD in Computer Science, UCL

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 Germany, Iceland, France and the US, amongst other places, in large-scale data analysis. The finance sector has also hired several graduates recently.

Careers data is taken from the ‘Destinations of Leavers from Higher Education’ survey undertaken by HESA looking at the destinations of UK and EU students in the 2013–2015 graduating cohorts six months after graduation.

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.

Research Excellence Framework (REF)

The Research Excellence Framework, or REF, is the system for assessing the quality of research in UK higher education institutions. The 2014 REF was carried out by the UK's higher education funding bodies, and the results used to allocate research funding from 2015/16.

The following REF score was awarded to the department: Computer Science

96% rated 4* (‘world-leading’) or 3* (‘internationally excellent’)

Learn more about the scope of UCL's research, and browse case studies, on our Research Impact website.



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Learn how to research, design and develop machine learning and autonomous systems technologies. You’ll be prepared for a wide range of careers in industry. Read more

Learn how to research, design and develop machine learning and autonomous systems technologies. You’ll be prepared for a wide range of careers in industry.

Intelligent and autonomous systems are increasingly important in all areas of human life and activity from medicine and space exploration to agriculture and entertainment.

Understanding and developing autonomous systems involves a range of skills and knowledge including designing interactive systems with both human and machine elements, and modelling and building systems that can sense and learn.

Machine learning is at the heart of autonomous and intelligent systems, including computer vision and robotics. It also underpins the recent developments in data analytics across many fields.

You will learn to use new knowledge to solve complex machine learning and autonomous systems problems. You’ll develop a range of skills including the theory of machine learning, artificial intelligence, autonomous systems design and engineering, and the implications for humans of interacting more and more with intelligent and autonomous systems.

You will be taught by academics from the Department of Computer Science with expertise in machine learning, autonomous systems, artificial intelligence and human-computer interaction. This course has been designed in collaboration with the Department of Electronic and Electrical Engineering who offer expertise in robotics.

You will study in a research-led department with a supportive postgraduate community. You’ll learn in our bespoke computer laboratory and be exposed to the latest ideas and technology. The department has strong links to industry both nationally and internationally.

With machine learning and autonomous systems forming an essential part of a number of key industries, our MSc graduates will be highly sought after by employers.

You’ll gain the knowledge and transferable skills for a career in a wide range of industries, or for further study at PhD level. Graduates from the department have gone on to work in a wide variety of sectors, including IT consultancy, software development, banking and education.

Visit the website.



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This course is designed to meet the needs of electrical, electrical power, electronic and telecommunication engineers who are looking to open up their career prospects. Read more
This course is designed to meet the needs of electrical, electrical power, electronic and telecommunication engineers who are looking to open up their career prospects. You will specialise in one of three majors: Emerging Power Systems, Telecommunication and Networking, or Embedded Systems. Among a wide range of optional units, you may study electrical power, renewable energy, communications and computer engineering at the system level and the component level.

The course is designed to allow you to undertake further studies in a field of your preference through advanced coursework and a major project, ultimately developing a prototype and presenting a formal thesis on the outcome. With the approval of the course coordinator, you may also include a unit from the Curtin Business School, or the Department of Computing, or the Department of Mathematics and Statistics.

EMERGING POWER SYSTEMS (314675)

Global demands on resources have placed an urgent emphasis on supplying a growing population with affordable, environmentally responsible power. How we manage this challenging paradigm will rely on a new generation of creative, technically savvy engineers. Since fossil fuels are a finite resource, the development of alternative sources of electrical energy such as solar and wind is vital.

The challenges that face you as a power engineer include interfacing renewable sources to the electricity distribution system, maintaining stability in the presence of many small energy sources and guaranteeing an electrical supply in the presence of intermittent sources such as solar power.

This major addresses challenges in the generation, transmission and distribution of electricity. Emergent technologies like smart grid and distributed generation are covered in detail. You will have the opportunity to further investigate and apply emergent technologies through your project work.

TELECOMMUNICATIONS AND NETWORKING (314676)

The electronics and communication fields represent two of the greatest growing technology areas in the world. With the rapid progress of information technology, the role of communications is becoming even more crucial for increasing industry efficiency and competition – whether machine talking to machine, computer with computer or human with human via a wide array of methods.

This major explores relevant topics in telecommunications and networking like mobile radio communications and data network security. The wide range of optional units includes topics such as computer architectural philosophies, LAN and WAN technologies, electromagnetics, error control coding, troubleshooter management, legal frameworks, and system design. You will also have the opportunity to further investigate a specialist area and apply your skills and knowledge through your project work.

EMBEDDED SYSTEMS (314677)

Our world is characterised by the ever-increasing number of intelligent devices which have inbuilt or 'embedded' computers. Computers in the form of microprocessors are being embedded in almost every other form of system to control them or provide additional services, creating a strong demand for electrical engineers in all industrially advanced nations.

In this major, you will study intermediate and advanced topics in embedded systems, for example, embedded systems in field-programmable gate arrays (FPGAs) and embedded software engineering. You will have the opportunity to further investigate and apply emergent technologies in embedded systems through your chosen advanced project.

Credit for previous study

Applications for recognition of prior learning (RPL) are assessed on an individual basis.

2016 Curtin International Scholarships: Merit Scholarship

Curtin University is an inspiring, vibrant, international organisation, committed to making tomorrow better. It is a beacon for innovation, driving advances in technology through high-impact research and offering more than 100 practical, industry-aligned courses connecting to workplaces of tomorrow.

Ranked in the top two per cent of universities worldwide in the Academic Ranking of World Universities 2015, the University is also ranked 25th in the world for universities under the age of 50 in the QS World University Rankings 2015 Curtin also received an overall five-star excellence rating in the QS stars rating.

Curtin University strives to give high achieving international students the opportunity to gain an internationally recognised education through offering the Merit Scholarship. The Merit Scholarship will give you up to 25 per cent of your first year tuition fees and if you enrol in an ELB program at Curtin English before studying at Curtin, you will also receive a 10 per cent discount on your Curtin English fees.

For full details and terms and conditions of this scholarship, please visit: curtin.edu/int-scholarships and click on Merit.

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The MS program in Electrical and Electronics Engineering aims to provide advanced education and a cutting edge research experience in electrical and electronics engineering, or in electrical and computer engineering crossing the boundary of the two disciplines. Read more
The MS program in Electrical and Electronics Engineering aims to provide advanced education and a cutting edge research experience in electrical and electronics engineering, or in electrical and computer engineering crossing the boundary of the two disciplines. The focus of this program is excellence in research. Graduates of the program can join industry or continue to work in academia.

Current faculty projects and research interests:

• Micro and Nano Systems (MEMS & NEMS)
• Wireless, Acoustic, Nano and Quantum Communication
• Waves, Optics and Photonics
• Electrical, Biological and Nano-Scale Systems
• Signal, Speech, Image and Video Processing
• Multimedia and Networking
• Machine Learning

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The control and conversion of electric power using solid-state techniques are now commonplace in both the domestic and industrial environments. Read more
The control and conversion of electric power using solid-state techniques are now commonplace in both the domestic and industrial environments. A knowledge and understanding of the diverse disciplines encompassed by Power Electronics: devices, converters, control theory and motor drive systems, is now essential to all power engineers. Power electronics, driven by the need for greater energy efficiency and more accurate control of a wide range of systems, is developing rapidly.

This course aims to provide specialist education in power electronics and drive techniques, covering key fundamental principles along with modern applications and current practices. It provides a specialist education in power electronics and drives techniques, covering key fundamental principles along with modern applications and current practices.

Students will develop:

the analytical and critical powers for the development of hardware and software required for power electronics and drives
the ability to plan and undertake an individual project
interpersonal, communication and professional skills
the ability to communicate ideas effectively in written reports
the technical skills to equip them for a leading career in power electronics or electrical machine drive systems
an understanding of how power electronics are applied within key industries such as aerospace and power supply

Following the successful completion of the taught modules, an individual research project is undertaken during the summer term.

Previous research projects on this course have included:

Development of a microprocessor controlled variable speed permanent magnet motor for an aerospace application
Experimental determination of induction motor torque-speed curves under variable speed
Evaluation of stray reactance in a current source rectifier for marine propulsion motor drives and wind power generators
Design, build and testing of a DSP-controlled switched reluctance motor for an automotive power assisted steering application

Scholarship information can be found at http://www.nottingham.ac.uk/graduateschool/funding/index.aspx

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This course delivers a broad coverage of all major disciplines in Electrical Power, including power electronics, electric drives, electrical machine design and power systems. Read more
This course delivers a broad coverage of all major disciplines in Electrical Power, including power electronics, electric drives, electrical machine design and power systems. It also covers important electrical power themes such as renewable energy systems and electric vehicles.

The Electrical Power MSc covers the following key subject areas:
-Electrical Machines
-Power Electronics
-Electric Drives
-Power System Operation
-Control of Electrical Power

A feature of the course is design of electrical systems for transportation and renewable energy applications. This is a particular specialisation of researchers in the School of Electrical and Electronic Engineering.

You will develop a knowledge of industry standard computer aided design and analysis techniques appropriate to electrical power such as the use of software packages such as MagNet, MATLAB, Simulink, PSpice and ERACS.

Throughout the course you use industry standard test and measurement equipment, experimental hardware, and software packages relevant to the field of electrical and power engineering.

The course comprises a mixture of lectures, tutorials, coursework and practical laboratory classes. You will research a specialist topic of your choice through an in-depth project. Innovative educational techniques are designed to equip you with practical design skills and research methodologies.

As a graduate of this course you are equipped with the knowledge and practical experience to embark on a career as an engineer in the field of Electrical Power. You will also have skills in research and knowledge acquisition and a solid foundation for further postgraduate studies in the field of electrical engineering and power engineering.

Delivery

You take modules to a total value of 180 credits over three semesters. Taught modules, worth 120 credits, take place during the first and second semesters with exams held in January and May/June. An individual project, worth 60 credits, is undertaken over semesters two and three.

Background reading and design work take place during the second semester. The majority of experimental work and preparation of your dissertation takes place during the semester three.

Teaching takes place in lecture theatres equipped with audio visual equipment. Blackboard, a web based Virtual Learning Environment (VLE) supports your taught modules. Practical sessions are in small groups with experts in the field of Power Electronics, Electric Drives, Machines, and Power Systems and in modern laboratory and computing facilities.

Employability

We collect information from our graduates six months after they leave University. This is part of the Destination of Leavers from Higher Education (DLHE) survey that every UK higher education institution takes part in.

Accreditation

The course is accredited by the Institution of Engineering and Technology (IET) and Engineering Council, and therefore provides a good foundation for professional registration.

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The MRes Electrical Power and Energy Technology programme provides advanced and systematic education and training in the areas of electronic science and technology. Read more

The MRes Electrical Power and Energy Technology programme provides advanced and systematic education and training in the areas of electronic science and technology. It has been designed to respond to the vigorous development of electric power and energy technology in China and worldwide.

The programme contains taught courses covering solar converters, wind power systems, energy storage technology, and smart grids. It places strong emphasis on hands-on experience and practical skills development. A 12-month extensive research project is required which leads to submission of a dissertation after students have finished the taught modules.

You will develop the understanding of state-of-the-art electrical power and energy technology; be able to research and critically evaluate trends in current technologies of energy management, sustainability, renewable energy and nuclear energy; skills in planning, project management and communicating complex ideas; and experience in conducting extended research and/or developing project work.

You will benefit from:

  • excellent research platform equipped with advanced experimental equipment, including network analyser, power analyser and electrical machine testing system etc.
  • cutting-edge research areas that aim for the intelligent and efficient utilisation of emerging electrical power and energy technologies
  • close cooperation with world famous universities and research centres to solve major challenges.
  • additional learning activities provided to improve students’ research and design skills, such as module CEN901 Research Methods (Information Management and Expression).


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In the course of the electronic revolution at the end of the 20th century, mechanical engineering was reinvented as the backbone of industrial production. Read more
In the course of the electronic revolution at the end of the 20th century, mechanical engineering was reinvented as the backbone of industrial production. The result is mechatronics, a synergistic combination of mechanical components with electronic and IT systems. This technological integration forms new areas of application like electrical and digital technology in machine communication and control.

With the introduction of the Master program in Mechatronics & Smart Technologies, MCI has filled a gap in the educational offering in the west of Austria. With its international orientation and a consistent focus on practical relevance, the program makes a significant contribution to the goal of establishing the Tyrol as a high-tech location with the ability to compete at the international level and defy the fluctuations of the business cycle. With the implementation of the majors in mechanical and electrical engineering and the specialization in computational mechanics at our partner campus in Paris, MCI continues its way as spear head of the Tyrolean technology offensive.

The goal of the Master program in particular is to equip graduates with a competence in mechatronics that is more than the sum of its parts, i.e. mechanical engineering, electronics and IT. Integration of these three pillars is the key to smart technologies as robotics, automated code generation, multi-physical simulation, systems in systems and smart automation, and their application in electro mobility, industry 4.0 and energy efficiency.

With supporting classes in Leadership, Strategic Management, Marketing and Entrepreneurship, this study program opens up perspectives for knowledge-based careers in the manufacturing and service industries worldwide.

Contents

The Master program in Mechatronics & Smart Technologies lasts four semesters comprising 915 hours of classes.

A semester of the full-time program comprises 15 weeks of lectures. The winter semester starts at the beginning of October until the end of January and the summer semester starts in March and lasts until the end of June.
Classes are entirely taught in English, attendance is required from Monday to Friday with additional block classes as well as project and laboratory work.

For the part-time program, the semesters last 20 weeks, from the beginning of September until the middle of February for the winter semester, and from the end of February until the middle of July for the summer semester. Classes are mainly taught in German but also partly in English. Attendance is required on Fridays from 1.30 to 10 p.m. and on Saturdays from 8 a.m. to 5 p.m., and there are additional block classes as well as project and laboratory work, etc.

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Application period/deadline. November 1, 2017 - January 24, 2018. Research-oriented degree provides an exciting opportunity to study in a leading-edge research environment. Read more

Application period/deadline: November 1, 2017 - January 24, 2018

• Research-oriented degree provides an exciting opportunity to study in a leading-edge research environment

• The studies combine both theoretical and practical approach

• Specializations in Applied Computing, Artificial Intelligence, and Computer Egineering

The International Master’s Degree Programme in Computer Science and Engineering (CSE) is a two-year research-oriented programme concentrating on intelligent digital solutions to real world problems. During the past decades, Computer Science and Engineering has had a significant impact into our daily lives. The development continues and soon computers will not be used as separate devices anymore. Instead they will blend into our living environments and offer us rich sets of services through natural and intuitive user interfaces. The graduates from Computer Science and Engineering will play a key role in this development.

The two-year programme has three specialisation options:

• Applied Computing

• Artificial Intelligence

• Computer Engineering

Applied Computing focuses on the next generation of interactive systems that place humans at the focus of the technological development. Adopting a multidisciplinary real-world approach, students have to spend a substantial amount of time working in group projects to develop a variety of systems ranging from interactive online services to games and mobile applications, with a strong focus on innovation and design.

Artificial Intelligence focuses in various fields of AI, such as machine learning, machine vision, and data mining. This specialisation provides students with a solid theoretical understanding and practical skills on processing and analyzing digital data and the ability to create intelligent solutions to real world problems with modern AI techniques.

Computer Engineering focuses on both hardware and software aspects of computing with emphasis on embedded system development. In this specialisation, students also study signal processing and its applications, and work with projects on modern signal processors and embedded computers. The specialisation gives the students a good basis to work with Internet of Things (IoT) applications.

In addition to the core specialization options, students can take optional courses to widen their specialization expertise into:

• Biomedical signal analysis

• Machine learning

• Machine vision

• Signal processing

• Embedded systems

• Ubiquitous computing

This Master’s programme is provided by the Faculty of Information Technology and Electrical Engineering, and students are strongly encouraged to work closely with research groups in the faculty that are international leaders in their fields. The Center for Machine Vision and Signal Analysis (CMVS) is renowned world-wide for its 35 years of expertise in computer vision research. The Center for Ubiquitous Computing (UBICOMP) has created a unique research environment for Ubiquitous Computing including multitouch wall-sized displays, smartphone sensing middleware and sensor networks. Biomimetics and Intelligent Systems Group (BISG) is a fusion of expertise from the fields of computer science and biology. During the studies the research groups provide students trainee and master’s thesis positions, with the possibility to continue as a doctoral student, and even as a post-doctoral researcher.

The programme will provide the graduates with sufficient skills to work in a wide variety of positions offered by research institutes and companies mainly operating in the field of information and communications technology (ICT). The graduates are most likely to be employed in research and development related positions, but also management positions and entrepreneurship fit into the profile.

Possible titles include:

• Research Scientist

• Software Engineer

• System Designer

• Project Manager

• Specialist

Students applying for the programme must possess an applicable B.Sc. degree in computer science, electrical engineering or relevant fields such as physics or applied mathematics.

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Taking BEng (Hons) Robotics to the next level, this MEng course digs deeper into the robotic technologies that are shaping today and tomorrow. Read more
Taking BEng (Hons) Robotics to the next level, this MEng course digs deeper into the robotic technologies that are shaping today and tomorrow. Providing an extra year of insight and training, your learning will be informed by robotics research pushing boundaries worldwide led by our very own teaching staff. You’ll build technical and managerial skills that you can put into practice daily, through a final group project that will set your course for success when you graduate.

You will experience learning that meets the highest standard academic requirements set by The Institution of Engineering and Technology (IET). You will draw on unique opportunities to engage in world-class robotics research, and in a variety of activities. You’ll capitalise on the opportunity to take a work placement in your second or third year, putting your robotics skills into action in the real world. You will take the fastest route to Chartered Engineer status.

Key features

-Benefit from outstanding teaching: in the 2016 National Student Survey 93 per cent of our final year students said that “The course is intellectually stimulating”.*
-Immerse yourself in a degree accredited by the Institution for Engineering and Technology (IET) on behalf of the Engineering Council for the purposes of fully meeting the academic requirement for registration as a Chartered Engineer (CEng).
-Keep pace with the fast-moving world of robotics, on a course that cuts a path through the latest research across technologies and disciplines.
-Take the fastest route to Chartered Engineer status.
-Experience learning that meets the highest standard academic requirements set by The Institution of Engineering and Technology (IET).
-Undertake a major robotics design and implementation in your final project, showcasing your technical and managerial skills. Develop your technical content, legal and business skills as well as team working and project planning.
-Capitalise on the opportunity to take a work placement in your second or third year, putting your robotics skills into action in the real world.
-Rise to the challenge as part of the Plymouth Humanoids team, battling it out in a variety of international robot competitions.
-Develop professional writing skills as well as strengthening your technical design skills.
-Refine your professional project management skills, with dedicated professional support from staff across the entire final year on every different aspect of your project.
-Work alongside internationally-renowned staff in a leading service and cognitive robotics research environment.
-Draw on unique opportunities to engage in world-class robotics research, and in a variety of activities (for example, in the humanoid robot football, Federation of International Robot-soccer Association (FIRA) competition).

Course details

Year 1
In your first year you'll learn through doing, developing your knowledge and practical problem solving skills in our dedicated robotics and communications laboratories. From analogue and digital electronics to engineering mathematics, you'll build up the essential foundations of robotics. Group project work will also help you develop your communication skills and you'll learn structured design procedures for hardware and software all brought together in an integrating robotics project.

Core modules
-ELEC143 Embedded Software in Context
-BPIE112 Stage 1 Electrical/Robotics Placement Preparation
-ELEC141 Analogue Electronics
-ELEC142 Digital Electronics
-ELEC144 Electrical Principles and Machines
-MATH187 Engineering Mathematics

Optional modules
-ELEC137PP Electronic Design and Build
-ROCO103PP Robot Design and Build

Year 2
Throughout your second year, you'll develop a greater understanding of underlying engineering principles and circuit design methods. Again there's an emphasis on team-work, with the opportunity to do both group and individual presentations of your projects. You'll use industrial standard software tools for design and simulation, data monitoring and control, all valuable preparation for your final year individual project or for a placement year.

Core modules
-MATH237 Engineering Mathematics and Statistics
-ROCO222 Introduction to Sensors and Actuators
-BPIE212 Stage 2 Electrical/Robotics Placement Preparation
-ROCO224 Introduction to Robotics
-ROCO218 Control Engineering
-ELEC240 Embedded Systems
-ELEC241 Real Time Systems

Optional placement year
Your optional work placement experience gives opportunities to put theory into practice, grow your understanding of robotics in the real world and showcase your growing expertise. We can help you find industrial placement opportunities in the UK, France, Germany or even Japan. Placements will complement your studies with on-the-ground experience and could lead to final year sponsorship. Many of our graduates are offered permanent jobs with their placement company.

Core modules
-BPIE332 Electrical Industrial Placement

Year 4
This is when your skills, expertise and know how come into their own. Through your individual project you'll consolidate your knowledge, explore and evaluate new technologies and showcase your potential. You'll demonstrate your communication skills in an oral and written presentation of your project. Refining the independent learning skills you've developed throughout the course, you'll build a proactive, imaginative and dynamic approach to learning, vital for your future robotics career.

Core modules
-ROCO318 Mobile and Humanoid Robots
-PROJ324 Individual Project
-ELEC351 Advanced Embedded Programming
-AINT308 Machine Vision and Behavioural Computing

Optional modules
-ELEC345 High Speed Communications
-AINT351 Machine Learning

Final year
The MEng includes additional technical modules and a large interdisciplinary design project. There is also the possibility of continuing your studies to MSc level in the same academic year.

Core modules
-ROCO503 Sensors and Actuators
-ROCO504 Advanced Robot Design
-PROJ515 MEng Project
-AINT512 Science and Technology of Human-Robot Interaction

Every undergraduate taught course has a detailed programme specification document describing the course aims, the course structure, the teaching and learning methods, the learning outcomes and the rules of assessment.

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Your programme of study. If you want to get involved in our next industry revolution - Industry 4.0 this degree will go a long way to providing you with many skills needed in this high growth industry area which has continued from where the mass communications revolution. Read more

Your programme of study

If you want to get involved in our next industry revolution - Industry 4.0 this degree will go a long way to providing you with many skills needed in this high growth industry area which has continued from where the mass communications revolution. You must have covered either computer science or electrical and electronic engineering as your first degree or a suitable combination to study this Master's degree. The digital age is changing the way we live, communicate, interact and our quality of life rapidly. Cloud based networks are now normal, autonomous vehicles are being explored, visual recognition, GIS aligning to our search interests, data mining to inform us automatically at any point in time what is happening around us and new methods to inform us of danger, awareness, alerts and so on.

Artificial Intelligence provides in depth knowledge of data mining, natural language, information visualisation and communication used in Industry 4.0 innovation industries such as autonomous vehicles, sensor data collection and computation, visual computer recognition software and machine to machine technologies. It is also said that artificial intelligence has the potential to change how we research and act to provide immediate solutions to energy, travel, and gridlock before it happens by setting up more alerts and warnings to us. We now already have the capabilities in smart technology to alert us on maps, apps, weather stations, lighting, sensors and other electronic and wired machine to machine devices to provide instant relevant information.

You are also advised to visit the organisation websites via the link below to find out about the innovations which may be influenced by AI:

Scottish Innovation Centres -

Courses listed for the programme

SEMESTER 1

Compulsory Courses

  • Foundations in AI
  • Machine Learning
  • Evaluation Systems of AI Systems
  • Engineering of AI Systems

SEMESTER 2

Compulsory Courses

  • Data Mining and Visualisation
  • Natural Language Generation
  • Software Agents and Multi-Agent Systems
  • Knowledge Representation and Reasoning

SEMESTER 3

You can broaden and deepen your skills with industry client opportunities where possible

Find out more detail by visiting the programme web page

Why study at Aberdeen?

  • AI or Artificial Intelligence is part of a major industrial revolution globally, linking to the Internet of Things
  • Aberdeen gives you a strong worldwide reputation for teaching in computing science, data science and natural language generation
  • You can be involved in cutting edge innovations which will shape our world in the future

Where you study

  • University of Aberdeen
  • 12 Months Full Time
  • September start

International Student Fees 2017/2018

Find out about fees:

*Please be advised that some programmes have different tuition fees from those listed above and that some programmes also have additional costs.

Scholarships

View all funding options on our funding database via the programme page and the latest postgraduate opportunities

Living in Aberdeen

Find out more about:

  • Your Accommodation
  • Campus Facilities
  • Aberdeen City
  • Student Support
  • Clubs and Societies

Find out more about living in Aberdeen and living costs 

You may also be interested in:

Information Technology MSc - Campus or Online



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This is an MSc course in Embedded Systems with contributions from the fields of mechatronics and robotics. Embedded systems are microprocessor-based systems within a larger mechanical or electrical system that performs a dedicated function or task. Read more
This is an MSc course in Embedded Systems with contributions from the fields of mechatronics and robotics.

Embedded systems are microprocessor-based systems within a larger mechanical or electrical system that performs a dedicated function or task. They encompass a wide variety of products ranging from small mobile phones to large process automation installations. A practicing engineer in the field of embedded systems needs to have a specialised expertise in more than one of the engineering subjects of this multi-discipline subject.

Our MSc is tailored to provide you with advanced learning in microprocessor systems that are at the heart of embedded systems, with additional contributions from the fields of mechatronics and robotics. This approach reflects the needs of the industry and is well supported by the range in expertise we have in our Department.

The Department of Engineering and Design covers the full gamete of teaching in electronic, telecommunication and computer networks engineering as well as mechanical engineering and product design.

Our academics are a cohesive group of highly skilled lecturers, practitioners and researchers. You'll benefit from your choice of supervisors to support a wide range of modern and multi-discipline Masters-level projects. Our teaching is supported by well-equipped laboratory workshops, using mostly the latest hardware and software available in universities.

Modules

In each of the semesters 1 and 2 you will be required to take two core and one optional module from the lists below:

Semester 1:

•Robotics (20 credits)
• Microprocessors and Control (20 credits)

Optional modules (Semester 1):

• Pattern recognition and machine learning (20 credits)
• Technical, research and professional skills (20 credits)
• Advanced Instrumentation and Design (20 credits)
• Electrical Energy Converters and Drives (20 credits)

Semester 2:

• Digital Signal Processing and Real Time Systems (20 credits)
• Mechatronics and Embedded System Design (20 credits)

Optional modules (Semester 2):

• Electromechanical systems and manufacturing technology (20 credits)
• Technology evaluation and commercialisation (20 credits)
• Cloud Computing (20 credits)
• E-Business Applications (20 credits)

Semester 3

•MSc project (60 credits)

Professional links

The School of Engineering at LSBU has a strong culture of research, extensive research links with industry through consultancy works and Knowledge Transfer Partnerships (KTPs), and teaching content is closely related to the latest research findings in the field.

History and expertise

A strong research tradition and our industrial links has helped shaped the course design, content selection, course delivery and project supervision.

The Department of Engineering and Design has a strong Mechatronics, Robotics and Non-destructive testing research group with a wide national and international profile. This is in addition to excellent research in many areas of mechanical engineering, electrical engineering, product design, computer network and telecommunications engineering.

Employability

The course has been designed to help to meet the needs of industry. How much your employability will increase, will depend on your background and the personal contribution you make to your development whilst studying on the course.

Benefits for new graduates

If you are a new graduate in electronic or computer engineering then you benefit from the further advanced topics presented. You'll get an opportunity to cut your teeth on a challenging MSc Project, which will demonstrate your abilities to the potential employers. Alternatively, you could also pursue PhD studies after completing the course.

Benefits of returning to University

If you are returning to University after a period of working in industry, then you'll be able to update yourself with the recent technological progress in the field. You'll gain confidence in your ability to perform at your best and stand a better chance to seek challenging work opportunities. If you are already working in the field, the MSc qualification will enhance your status which will may help with your promotion.

Employment links

We are continually developing links with employers who are interested to provide internship to our students . Examples of this can include small VHDL and DSP designs, ARM based designs, industrial design or correlation research. These projects can be performed as part of the curriculum or as part of a research project.

LSBU Employability Services

LSBU is committed to supporting you develop your employability and succeed in getting a job after you have graduated. Your qualification will certainly help, but in a competitive market you also need to work on your employability, and on your career search. Our Employability Service will support you in developing your skills, finding a job, interview techniques, work experience or an internship, and will help you assess what you need to do to get the job you want at the end of your course. LSBU offers a comprehensive Employability Service, with a range of initiatives to complement your studies, including:

• Direct engagement from employers who come in to interview and talk to students
• Job Shop and on-campus recruitment agencies to help your job search
• Mentoring and work shadowing schemes.

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