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The programme is for students with computer science, mathematics, science or engineering backgrounds and good knowledge of computer programming. Read more
The programme is for students with computer science, mathematics, science or engineering backgrounds and good knowledge of computer programming. To improve ability to solve advanced computational problems by providing a thorough knowledge of data structures, design, quantitative analysis of algorithms and algorithmic applications and impart skills necessary for algorithm implementation within the overall context of software development.

Key benefits

- Unrivalled location in the heart of London giving access to major libraries and leading scientific societies, including the BCS Chartered Institute for IT, and the Institution of Engineering and Technology (IET).

- Equips graduates with practical techniques and implementation skills for solving advanced computational problems.

- Develops critical awareness and appreciation of the changing role of computing in society, motivating graduates to pursue continuing professinoal development and further research.

- Access to speakers of international repute through seminars and external lectures, enabling students to keep abreast of emerging knowledge in advanced computing and related fields.

Visit the website: http://www.kcl.ac.uk/study/postgraduate/taught-courses/advanced-computing-msc.aspx

Course detail

- Description

This programme provides students with systematic knowledge and experience of the theoretical foundations and practice of computing at an advanced level. It is built around taught core modules such as Algorithm Design and Analysis, Data Structures and their Implementation in C++, Parallel and Distributed Algorithms, which are complemented by a wide range of optional modules for multimedia, optimisation, string processing and the web. The final part of the programme is an individual project which is closely linked with the Department's research activities.

- Course purpose

For graduates in computer science, mathematics, science or engineering with good knowledge of computer programming, this MSc will enhance your ability to solve advanced computational problems and impart skills necessary for algorithm implementation. Research for your individual project will provide valuable preparation for a career in research or industry.

- Course format and assessment

Lectures; tutorials; seminars; laboratory sessions; optional career planning workshops. Assessed through: coursework; written examinations; final project report.

- Compulsory modules:

- Algorithm Design & Analysis
- Data Structures & their Implementation in C++
- Parallel & Distributed Algorithms.

Career prospects

Via the Department’s Careers Programme, students are able to network with top employers and obtain advice on how to enhance career prospects. Our graduates have gone on to have very successful careers in general software consultancy companies, in specialised software development companies and in IT departments of large institutions (financial, telecommunications and public sector). Their jobs involve specialist programming and problem solving as well more conventional software development, maintenance and project management roles. Our graduates have also entered into academic and industrial research in software engineering, bioinformatics, algorithms and computer networks.

How to apply: http://www.kcl.ac.uk/study/postgraduate/apply/taught-courses.aspx

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Life Sciences is one of the strategic research fields at the University of Helsinki. The multidisciplinary Master’s Programme in Life Science Informatics (LSI) integrates research excellence and research infrastructures in the Helsinki Institute of Life Sciences (HiLIFE). Read more
Life Sciences is one of the strategic research fields at the University of Helsinki. The multidisciplinary Master’s Programme in Life Science Informatics (LSI) integrates research excellence and research infrastructures in the Helsinki Institute of Life Sciences (HiLIFE). As a student, you will gain access to active research communities on three campuses: Kumpula, Viikki, and Meilahti. The unique combination of study opportunities tailored from the offering of the three campuses provides an attractive educational profile. The LSI programme is designed for students with a background in mathematics, computer science and statistics, as well as for students with these disciplines as a minor in their bachelor’s degree, with their major being, for example, ecology, evolutionary biology or genetics.

As a graduate of the LSI programme you will:
-Have first class knowledge and capabilities for a career in life science research and in expert duties in the public and private sectors.
-Competence to work as a member of a group of experts.
-Have understanding of the regulatory and ethical aspects of scientific research.
-Have excellent communication and interpersonal skills for employment in an international and interdisciplinary professional setting.
-Understand the general principles of mathematical modelling, computational, probabilistic and statistical analysis of biological data, and be an expert in one specific specialisation area of the LSI programme.
-Understand the logical reasoning behind experimental sciences and be able to critically assess research-based information.
-Have mastered scientific research, making systematic use of investigation or experimentation to discover new knowledge.
-Have the ability to report results in a clear and understandable manner for different target groups.
-Have good opportunities to continue your studies for a doctoral degree.

The University of Helsinki will introduce annual tuition fees to foreign-language Master’s programmes starting on August 1, 2017 or later. The fee ranges from 13 000-18 000 euros. Citizens of non-EU/EEA countries, who do not have a permanent residence status in the area, are liable to these fees. You can check this FAQ at the Studyinfo website whether or not you are required to pay tuition fees: https://studyinfo.fi/wp2/en/higher-education/higher-education-institutions-will-introduce-tuition-fees-in-autumn-2017/am-i-required-to-pay-tuition-fees/

Programme Contents

The Life Science Informatics Master’s Programme has six specialisation areas, each anchored in its own research group or groups.

Algorithmic Bioinformatics
Goes with the Genome-scale algorithmics, Combinatorial Pattern Matching, and Practical Algorithms and Data Structures on Strings research groups. This specialisation area educates you to be an algorithm expert who can turn biological questions into appropriate challenges for computational data analysis. In addition to the tailored algorithm studies for analysing molecular biology measurement data, the curriculum includes general algorithm and machine learning studies offered by the Master's Programmes in Computer Science and Data Science.

Applied Bioinformatics
Jointly with The Institute of Biotechnology and genetics. Bioinformatics has become an integral part of biological research, where innovative computational approaches are often required to achieve high-impact findings in an increasingly data-dense environment. Studies in applied bioinformatics prepare you for a post as a bioinformatics expert in a genomics research lab, working with processing, analysing and interpreting Next-Generation Sequencing (NGS) data, and working with integrated analysis of genomic and other biological data, and population genetics.

Biomathematics
With the Biomathematics research group, focusing on mathematical modelling and analysis of biological phenomena and processes. The research covers a wide spectrum of topics ranging from problems at the molecular level to the structure of populations. To tackle these problems, the research group uses a variety of modelling approaches, most importantly ordinary and partial differential equations, integral equations and stochastic processes. A successful analysis of the models requires the study of pure research in, for instance, the theory of infinite dimensional dynamical systems; such research is also carried out by the group.

Biostatistics and Bioinformatics
Offered jointly by the statistics curriculum, the Master´s Programme in Mathematics and Statistics and the research groups Statistical and Translational Genetics, Computational Genomics and Computational Systems Medicine in FIMM. Topics and themes include statistical, especially Bayesian methodologies for the life sciences, with research focusing on modelling and analysis of biological phenomena and processes. The research covers a wide spectrum of collaborative topics in various biomedical disciplines. In particular, research and teaching address questions of population genetics, phylogenetic inference, genome-wide association studies and epidemiology of complex diseases.

Eco-evolutionary Informatics
With ecology and evolutionary biology, in which several researchers and teachers have a background in mathematics, statistics and computer science. Ecology studies the distribution and abundance of species, and their interactions with other species and the environment. Evolutionary biology studies processes supporting biodiversity on different levels from genes to populations and ecosystems. These sciences have a key role in responding to global environmental challenges. Mathematical and statistical modelling, computer science and bioinformatics have an important role in research and teaching.

Systems Biology and Medicine
With the Genome-scale Biology Research Program in Biomedicum. The focus is to understand and find effective means to overcome drug resistance in cancers. The approach is to use systems biology, i.e., integration of large and complex molecular and clinical data (big data) from cancer patients with computational methods and wet lab experiments, to identify efficient patient-specific therapeutic targets. Particular interest is focused on developing and applying machine learning based methods that enable integration of various types of molecular data (DNA, RNA, proteomics, etc.) to clinical information.

Selection of the Major

During the first Autumn semester, each specialisation area gives you an introductory course. At the beginning of the Spring semester you are assumed to have decided your study direction.

Programme Structure

Studies amount to 120 credits (ECTS), which can be completed in two years according to a personal study plan.
-60 credits of advanced studies from the specialisation area, including a Master’s thesis, 30 credits.
-60 credits of other studies chosen from the programme or from other programmes (e.g. computer science, mathematics and statistics, genetics, ecology and evolutionary biology).

Internationalization

The Life Science Informatics MSc is an international programme, with international students and an international research environment. The researchers and professors in the programme are internationally recognized for their research. A significant fraction of the teaching and research staff is international.

As a student you can participate in an international student exchange programme, which offers the possibility to include international experience as part of your degree. Life Science Informatics itself is an international field and graduates can find employment in any country.

In the programme, all courses are given in English. Although the Helsinki region is very international and English is widely spoken, you can also take courses to learn Finnish via the University of Helsinki’s Language Centre’s Finnish courses. The Language Centre also offers an extensive programme of foreign language courses for those interested in learning new languages.

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This highly focused MSc explores some of the mathematics behind modern secure information and communications systems, specialising in mathematics relevant for public key cryptography, coding theory and information theory. Read more
This highly focused MSc explores some of the mathematics behind modern secure information and communications systems, specialising in mathematics relevant for public key cryptography, coding theory and information theory. During the course critical awareness of problems in information transmission, data compression and cryptography is raised, and the mathematical techniques which are commonly used to solve these problems are explored.

The Mathematics Department at Royal Holloway is well known for its expertise in information security and cryptography and our academic staff include several leading researchers in these areas. Students on the programme have the opportunity to carry out their dissertation projects in cutting-edge research areas and to be supervised by experts.

The transferable skills gained during the MSc will open up a range of career options as well as provide a solid foundation for advanced research at PhD level.

See the website https://www.royalholloway.ac.uk/mathematics/coursefinder/mscmathematicsofcryptographyandcommunications(msc).aspx

Why choose this course?

- You will be provided with a solid mathematical foundation and a knowledge and understanding of the subjects of cryptography and communications preparing you for research or professional employment in this area.

- The mathematical foundations needed for applications in communication theory and cryptography are covered including Algebra, Combinatorics Complexity Theory/Algorithms and Number Theory.

- You will have the opportunity to carry out your dissertation project in a cutting-edge research area; our dissertation supervisors are experts in their fields who publish regularly in internationally competitive journals and there are several joint projects with industrial partners and Royal Holloway staff.

- After completing the course former students have a good foundation for the next step of their career both inside and outside academia.

Department research and industry highlights

The members of the Mathematics Department cover a range of research areas. There are particularly strong groups in information security, number theory, quantum theory, group theory and combinatorics. The Information Security Group has particularly strong links to industry.

Course content and structure

You will study eight courses as well as complete a main project under the supervision of a member of staff.

Core courses:
Advanced Cipher Systems
Mathematical and security properties of both symmetric key cipher systems and public key cryptography are discussed as well as methods for obtaining confidentiality and authentication.

Channels
In this unit, you will investigate the problems of data compression and information transmission in both noiseless and noisy environments.

Theory of Error-Correcting Codes
The aim of this unit is to provide you with an introduction to the theory of error-correcting codes employing the methods of elementary enumeration, linear algebra and finite fields.

Public Key Cryptography
This course introduces some of the mathematical ideas essential for an understanding of public key cryptography, such as discrete logarithms, lattices and elliptic curves. Several important public key cryptosystems are studied, such as RSA, Rabin, ElGamal Encryption, Schnorr signatures; and modern notions of security and attack models for public key cryptosystems are discussed.

Main project
The main project (dissertation) accounts for 25% of the assessment of the course and you will conduct this under the supervision of a member of academic staff.

Additional courses:
Applications of Field Theory
You will be introduced to some of the basic theory of field extensions, with special emphasis on applications in the context of finite fields.

Quantum Information Theory
‘Anybody who is not shocked by quantum theory has not understood it' (Niels Bohr). The aim of this unit is to provide you with a sufficient understanding of quantum theory in the spirit of the above quote. Many applications of the novel field of quantum information theory can be studied using undergraduate mathematics.

Network Algorithms
In this unit you will be introduced to the formal idea of an algorithm, when it is a good algorithm and techniques for constructing algorithms and checking that they work; explore connectivity and colourings of graphs, from an algorithmic perspective; and study how algebraic methods such as path algebras and cycle spaces may be used to solve network problems.

Advanced Financial Mathematics
In this unit you will investigate the validity of various linear and non-linear time series occurring in finance and extend the use of stochastic calculus to interest rate movements and credit rating;

Combinatorics
The aim of this unit is to introduce some standard techniques and concepts of combinatorics, including: methods of counting including the principle of inclusion and exclusion; generating functions; probabilistic methods; and permutations, Ramsey theory.

Computational Number Theory
You will be provided with an introduction to many major methods currently used for testing/proving primality and for the factorisation of composite integers. The course will develop the mathematical theory that underlies these methods, as well as describing the methods themselves.

Complexity Theory
Several classes of computational complexity are introduced. You will discuss how to recognise when different problems have different computational hardness, and be able to deduce cryptographic properties of related algorithms and protocols.

On completion of the course graduates will have:
- a suitable mathematical foundation for undertaking research or professional employment in cryptography and/or communications

- the appropriate background in information theory and coding theory enabling them to understand and be able to apply the theory of communication through noisy channels

- the appropriate background in algebra and number theory to develop an understanding of modern public key cryptosystems

- a critical awareness of problems in information transmission and data compression, and the mathematical techniques which are commonly used to solve these problems

- a critical awareness of problems in cryptography and the mathematical techniques which are commonly used to provide solutions to these problems

- a range of transferable skills including familiarity with a computer algebra package, experience with independent research and managing the writing of a dissertation.

Assessment

Assessment is carried out by a variety of methods including coursework, examinations and a dissertation. The examinations in May/June count for 75% of the final average and the dissertation, which has to be submitted in September, counts for the remaining 25%.

Employability & career opportunities

Our students have gone on to successful careers in a variety of industries, such as information security, IT consultancy, banking and finance, higher education and telecommunication. In recent years our graduates have entered into roles including Principal Information Security Consultant at Abbey National PLC; Senior Manager at Enterprise Risk Services, Deloitte & Touche; Global IT Security Director at Reuters; and Information Security manager at London Underground.

How to apply

Applications for entry to all our full-time postgraduate degrees can be made online https://www.royalholloway.ac.uk/studyhere/postgraduate/applying/howtoapply.aspx .

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This course covers a wide range of topics from both applied and applicable mathematics and is aimed at students who want to study the field in greater depth, in areas which are relevant to real life applications. Read more
This course covers a wide range of topics from both applied and applicable mathematics and is aimed at students who want to study the field in greater depth, in areas which are relevant to real life applications.

You will explore the mathematical techniques that are commonly used to solve problems in the real world, in particular in communication theory and in physics. As part of the course you will carry out an independent research investigation under the supervision of a member of staff. Popular dissertation topics chosen by students include projects in the areas of communication theory, mathematical physics, and financial mathematics.

The transferable skills gained on this course will open you up to a range of career options as well as provide a solid foundation for advanced research at PhD level.

See the website https://www.royalholloway.ac.uk/mathematics/coursefinder/mscmathematicsforapplications.aspx

Why choose this course?

- You will be provided with a solid mathematical foundation and knowledge and understanding of the subjects of cryptography and communications, preparing you for research or professional employment in this area.

- The Mathematics Department at Royal Holloway is well known for its expertise in information security and cryptography. The academics who teach on this course include several leading researchers in these areas.

- The mathematical foundations needed for applications in communication theory and cryptography are covered including Algebra, Combinatorics Complexity Theory/Algorithms and Number Theory.

- You will have the opportunity to carry out your dissertation project in a cutting-edge research area; our dissertation supervisors are experts in their fields who publish regularly in internationally competitive journals and there are several joint projects with industrial partners and Royal Holloway staff.

- After completing the course students have a good foundation for the next step of their career both inside and outside academia.

Department research and industry highlights

The members of the Mathematics Department cover a range of research areas. There are particularly strong groups in information security, number theory, quantum theory, group theory and combinatorics. The Information Security Group has particularly strong links to industry.

Course content and structure

You will study eight courses and complete a main project under the supervision of a member of staff.

Core courses:
Theory of Error-Correcting Codes
The aim of this unit is to provide you with an introduction to the theory of error-correcting codes employing the methods of elementary enumeration, linear algebra and finite fields.

Advanced Cipher Systems
Mathematical and security properties of both symmetric key cipher systems and public key cryptography are discussed, as well as methods for obtaining confidentiality and authentication.

Main project
The main project (dissertation) accounts for 25% of the assessment of the course and you will conduct this under the supervision of a member of academic staff.

Additional courses:
Applications of Field Theory
You will be introduced to some of the basic theory of field extensions, with special emphasis on applications in the context of finite fields.

Quantum Information Theory
‘Anybody who is not shocked by quantum theory has not understood it' (Niels Bohr). The aim of this unit is to provide you with a sufficient understanding of quantum theory in the spirit of the above quote. Many applications of the novel field of quantum information theory can be studied using undergraduate mathematics.

Network Algorithms
In this unit you will be introduced to the formal idea of an algorithm, when it is a good algorithm and techniques for constructing algorithms and checking that they work; explore connectivity and colourings of graphs, from an algorithmic perspective; and study how algebraic methods such as path algebras and cycle spaces may be used to solve network problems.

Advanced Financial Mathematics
In this unit you will investigate the validity of various linear and non-linear time series occurring in finance and extend the use of stochastic calculus to interest rate movements and credit rating;

Combinatorics
The aim of this unit is to introduce some standard techniques and concepts of combinatorics, including: methods of counting including the principle of inclusion and exclusion; generating functions; probabilistic methods; and permutations, Ramsey theory.

Computational Number Theory
You will be provided with an introduction to many major methods currently used for testing/proving primality and for the factorisation of composite integers. The course will develop the mathematical theory that underlies these methods, as well as describing the methods themselves.

Complexity Theory
Several classes of computational complexity are introduced. You will discuss how to recognise when different problems have different computational hardness, and be able to deduce cryptographic properties of related algorithms and protocols.

On completion of the course graduates will have:
- knowledge and understanding of: the principles of communication through noisy channels using coding theory; the principles of cryptography as a tool for securing data; and the role and limitations of mathematics in the solution of problems arising in the real world

- a high level of ability in subject-specific skills, such as algebra and number theory

- developed the capacity to synthesise information from a number of sources with critical awareness

- critically analysed the strengths and weaknesses of solutions to problems in applications of mathematics

- the ability to clearly formulate problems and express technical content and conclusions in written form

- personal skills of time management, self-motivation, flexibility and adaptability.

Assessment

Assessment is carried out by a variety of methods including coursework, examinations and a dissertation. The examinations in May/June count for 75% of the final average and the dissertation, which has to be submitted in September, counts for the remaining 25%.

Employability & career opportunities

Our students have gone on to successful careers in a variety of industries, such as information security, IT consultancy, banking and finance, higher education and telecommunication. In recent years our graduates have entered into roles including Principal Information Security Consultant at Abbey National PLC; Senior Manager at Enterprise Risk Services, Deloitte & Touche; Global IT Security Director at Reuters; and Information Security Manager at London Underground.

How to apply

Applications for entry to all our full-time postgraduate degrees can be made online https://www.royalholloway.ac.uk/studyhere/postgraduate/applying/howtoapply.aspx .

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This programme is an advanced computer science course that also introduces core management theories and skills to an audience of scientists and engineers who already possess a good foundation in programming. Read more
This programme is an advanced computer science course that also introduces core management theories and skills to an audience of scientists and engineers who already possess a good foundation in programming. It will improve your ability to solve advanced computational problems by gaining knowledge of data structures, design quantitative analysis of algorithms and their applications and implementation.

Key benefits

• Unrivalled location in the heart of London giving access to major libraries and leading scientific societies, including the BCS Chartered Institute for IT, and the Institution of Engineering and Technology (IET).

• Equips graduates with practical techniques and implementation skills for solving advanced computational problems.

• Develops critical awareness and appreciation of the changing role of computing in society, motivating graduates to pursue continuing professinoal development and further research.

• Access to speakers of international repute through seminars and external lectures, enabling students to keep abreast of emerging knowledge in advanced computing and related fields.

Visit the website: http://www.kcl.ac.uk/study/postgraduate/taught-courses/advanced-computing-with-management-msc.aspx

Course detail

- Description

This programme provides students with systematic knowledge and experience of the theoretical foundations and practice of computing at an advanced level. It is built around taught core modules such as Algorithm Design and Analysis, Data Structures and their Implementation in C++, Parallel and Distributed Algorithms, which are complemented by a wide range of optional modules for multimedia, optimisation, string processing and the web. The programme also prepares students to take on certain, more senior roles in industry that require specialist management knowledge and problem solving skills related to Advanced Computing. The final part of the programme is an individual project which is closely linked with the Department's research activities.

- Course purpose

For graduates in computer science, mathematics, science or engineering with good knowledge of computer programming, this MSc will enhance your ability to solve advanced computational problems and impart skills necessary for algorithm implementation within the context of software development and with core management theories. Research for your individual project will provide valuable preparation for a career in research or industry.

- Course format and assessment

Lectures; tutorials; seminars; laboratory sessions; optional career planning workshops. Assessed through: coursework; written examinations; final project report.

Career prospects

Via the Department’s Careers Programme, students are able to network with top employers and obtain advice on how to enhance career prospects. Our graduates have gone on to have very successful careers in general software consultancy companies, in specialised software development companies and in IT departments of large institutions (financial, telecommunications and public sector). Their jobs involve specialist programming and problem solving as well more conventional software development, maintenance and project management roles. Our graduates have also entered into academic and industrial research in software engineering, bioinformatics, algorithms and computer networks.

How to apply: http://www.kcl.ac.uk/study/postgraduate/apply/taught-courses.aspx

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As a student of this master’s programme, you will develop a solid grasp of computer systems and networks through a broad, yet in-depth, training experience in the field of Computer Science and Engineering. Read more
As a student of this master’s programme, you will develop a solid grasp of computer systems and networks through a broad, yet in-depth, training experience in the field of Computer Science and Engineering.

You will acquire theoretical knowledge and engineering skills in:
Parallel and Distributed Systems
Computer Security and Dependability
Computer Systems Engineering
Communication Networks

Programme description

The programme instills a set of essential skills that prepare you to work in Information and Computing Technology (ICT).

Courses in Computer Networks, Fault Tolerant Computer Systems, Parallel and Distributed Systems, Computer Architecture, Computer Security, and Real-Time Systems are taught by internationally recognised faculty in Computer Science and Engineering. In addition to academic training in skills related to algorithm design, programming languages and computer systems engineering, you will gain hands-on experience with emerging technologies and have opportunities to participate in cutting-edge research.

This programme is the first within Chalmers to provide the necessary preparation to contribute to ubiquitous computing, cyber-physical systems, and other rapidly growing areas in the expanding ICT industry. If you are interested in becoming a technology expert in these and other areas, the programme provides excellent background for pursuing doctoral studies.

Why apply

You will learn the design methodologies used to construct computer systems and networks. Such methodologies include Fault-Tolerant Distributed Algorithm Design, Concurrent Programming, Computer Systems Engineering, Systems Programming, and Secure and Dependable Systems Design. The coursework is designed to develop both your theoretical knowledge and practical expertise.

For example, you will learn how to:

design a system based on new and existing components (Systems Engineering)
understand low-level hardware/software interaction, develop systems and applications (Programming)
analyse performance and system design limitations (Distributed Computing) and
assess, evaluate, and design systems, programs and applications to increase security and dependability (Systems Design).

Rather than concentrating on a single aspect of computer systems and networks, the courses provide the broad, practical and up-to-date experience required by major ICT companies who develop computer systems and networks.

Who should apply

The programme trains professionals in the field of Computer Science and Engineering. We welcome applications from graduates of Computer Science, Computer Engineering, Information Engineering, Software Engineering, Electrical Engineering, Mechatronics, Mathematics and Physics.

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Modern information systems continue to transform and progress the ease with which information can be accessed across the globe and to underpin the digital society and economy. Read more
Modern information systems continue to transform and progress the ease with which information can be accessed across the globe and to underpin the digital society and economy.

They depend fundamentally on digital systems of communication, and this programme provides thorough coverage of the speciality to meet the high and increasing demand for digital communications engineers who can manage and develop the technologies of today’s data-driven lifestyle.

This programme is aimed at recent engineering, physics and computer science graduates and/or those with a number of years industry experience in the communications industry, who wish to acquire in-depth knowledge of this key specialism in order to progress their careers.

Core study areas include fundamentals of digital signal processing and information theory and coding, and a research project.

Optional study areas include communication networks, personal radio communications, communication channels, digital signal processing for software defined radio, multimedia over networks, mobile network technologies and intelligent signal processing.

See the website http://www.lboro.ac.uk/study/postgraduate/programmes/departments/eese/digital-communication-systems/

Programme modules

Compulsory Modules:
Semester 1
- Fundamentals of Digital Signal Processing
- Information Theory and Coding

Semester 2
- Research project
- Advanced individual project

Optional Modules:
Semester 1
- Communication Networks
- Personal Radio Communications
- Communication Channels

Semester 2
- Digital Signal Processing for Software Defined Radio
- Communication Network Security and e-Commerce
- Mobile Network Technologies
- Intelligent Signal Processing

How you will learn

The course is designed to give both deep understanding of the core technologies which underpin the industry and which are driving the latest advances in performance and capability. It allows you to develop your personal interests via a range of specialised optional modules. The individual research project is often undertaken as part of the School’s internationally respected research portfolio.

- Assessment
Examinations are held in January and May, with coursework and group work throughout the programme. The individual research project is assessed by written report and viva voce in September.

Facilities

Students on the programme have access to laboratories, industry standard software and hardware including equipment provided by Texas Instruments. There is a range of anechoic chambers including the largest microwave chamber at any UK university.

Careers and further study

Job opportunities include both senior technical and managerial activities in the fields of communications engineering including high speed digital design, communication systems engineering, software/firmware engineering, algorithm development and signal processing engineering.

Why choose electronic, electrical and systems engineering at Loughborough?

We develop and nurture the world’s top engineering talent to meet the challenges of an increasingly complex world. All of our Masters programmes are accredited by one or more of the following professional bodies: the IET, IMechE, InstMC, Royal Aeronautical Society and the Energy Institute.

We carefully integrate our research and education programmes in order to support the technical and commercial needs of society and to extend the boundaries of current knowledge.

Consequently, our graduates are highly sought after by industry and commerce worldwide, and our programmes are consistently ranked as excellent in student surveys, including the National Student Survey, and independent assessments.

- Facilities
Our facilities are flexible and serve to enable our research and teaching as well as modest preproduction testing for industry.
Our extensive laboratories allow you the opportunity to gain crucial practical skills and experience in some of the latest electrical and electronic experimental facilities and using industry standard software.

- Research
We are passionate about our research and continually strive to strengthen and stimulate our portfolio. We have traditionally built our expertise around the themes of communications, energy and systems, critical areas where technology and engineering impact on modern life.

- Career prospects
90% of our graduates were in employment and/or further study six months after graduating. They go on to work with companies such as Accenture, BAE Systems, E.ON, ESB International, Hewlett Packard, Mitsubishi, Renewable Energy Systems Ltd, Rolls Royce and Siemens AG.

Find out how to apply here http://www.lboro.ac.uk/study/postgraduate/programmes/departments/eese/digital-communication-systems/

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Ranked 2nd in the UK by Research Fortnight, our geomatics research is ground breaking. We publish in leading international journals, at conferences, in the media and through educational outreach programmes. Read more
Ranked 2nd in the UK by Research Fortnight, our geomatics research is ground breaking. We publish in leading international journals, at conferences, in the media and through educational outreach programmes. Whether focusing on geodesy or geospatial engineering, you will work with experts to produce research of an international standard.

The School of Civil Engineering and Geosciences enjoys an international reputation for using the latest science to solve problems of global importance. Our research has significant relevance in non-academic settings and we regularly apply it through consultancy to industry, from the global offshore industry to local authorities and survey and engineering companies. We are a key part of the TSB Satellite Applications Catapult North East Centre of Excellence.

For geomatics we have MPhil and PhD supervision in the following areas:

Satellite geodesy

-GPS and geophysical modelling
-GPS/GNSS geodesy
-Precise orbit determination of altimetric and geodetic satellites
-Sea level
-Ice sheet mass balance
-Satellite altimetry
-Static and temporal gravity field and reference frame analyses from dedicated satellite missions
-SAR interferometry
-Geophysical and industrial deformation monitoring
-Geodynamics and geohazards
-Integration of GPS and INS
-Engineering geodesy

Geospatial Engineering

-Geoinformatics and advanced GIS
-Geospatial algorithm development
-Spatial modelling including network modelling, cellular automata and agent based approaches to spatial complexity
-Multimedia cartography and information delivery
-Temporal GIS
-Geospatial data management
-Airborne and satellite remote sensing applied to environmental impact assessment
-Land use, vegetation and pollution monitoring
-Earth observation of urban systems
-Photogrammetry
-Laser scanning
-Precise non-contact dimensional control

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The accredited Master of Science program in Computer Science is a two-year program that has been designed for international and German graduate students. Read more
The accredited Master of Science program in Computer Science is a two-year program that has been designed for international and German graduate students. The curriculum is very flexible. Students can compile their individual study plans based on their background and interests. It is also a very practical program. In addition to lectures and tutorials, students will complete two seminars, one or two projects and the master thesis.

In the beginning students will choose one or two key courses. Key courses are courses which introduce the students to the research areas represented at the Department of Computer Science. The following key courses are offered:

• Algorithm Theory
• Pattern Recognition
• Databases and Information Systems
• Software Engineering
• Artificial Intelligence
• Computer Architecture

After that, students can specialize in one of the following three areas:

• Cyber-Physical Systems
• Information Systems
• Cognitive Technical Systems

Here are some examples of subjects offered in the three specialization areas:

Cyber-Physical Systems:

• Cyber-Physical Systems – Discrete Models
• Cyber-Physical Systems – Hybrid Control
• Real Time Operation Systems and Reliability
• Verification of Embedded Systems
• Test and Reliability
• Decision Procedures
• Software Design, Modeling and Analysis in UML
• Formal Methods for Java
• Concurrency: Theory and Practice
• Compiler Construction
• Distributed Systems
• Constraint Satisfaction Problems
• Modal Logic
• Peer-to-Peer Networks
• Program Analysis
• Model Driven Engineering

Information Systems:

• Information Retrieval Data Models and Query Languages
• Peer-to-Peer Networks
• Distributed Storage
• Software Design, Modeling and Analysis in UML
• Security in Large-Scale Distributed Enterprises
• Machine Learning
• Efficient Route Planning
• Bioinformatics I
• Bioinformatics II
• Game Theory
• Knowledge Representation
• Distributed Systems

Cognitive Technical Systems:

• Computer Vision I
• Computer Vision II
• Statistical Pattern Recognition
• Mobile Robotics II
• Simulation in Computer Graphics
• Advanced Computer Graphics
• AI Planning
• Game Theory
• Knowledge Representation
• Constraint Satisfaction Problems
• Modal Logic
• Reinforcement Learning
• Machine Learning
• Mobile Robotics I

We believe that it is important for computer science students to get a basic knowledge in a field in which they might work after graduation. Therefore, our students have the opportunity to complete several courses and/or a project in one of the following application areas:

• Bioinformatics
• Educational Sciences
• Geosciences
• Cognitive Sciences
• Mathematics
• Medicine
• Meteorology
• Microsystems Engineering
• Physics
• Political Sciences
• Psychology
• Sociology
• Economics

In the last semester, students work on their master’s thesis. They are expected to tackle an actual research question in close cooperation with a professor and his/her staff.

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Scientific computing is a new and growing discipline in its own right. It is concerned with harnessing the power of modern computers to carry out calculations relevant to science and engineering. Read more

Overview

Scientific computing is a new and growing discipline in its own right. It is concerned with harnessing the power of modern computers to carry out calculations relevant to science and engineering.
By its very nature, scientific computing is a fundamentally multidisciplinary subject. The various application areas give rise to mathematical models of the phenomena being studied.

Examples range in scale from the behaviour of cells in biology, to flow and combustion processes in a jet engine, to the formation and development of galaxies. Mathematics is used to formulate and analyse numerical methods for solving the equations that come from these applications.

Implementing the methods on modern, high performance computers requires good algorithm design to produce efficient and robust computer programs. Competence in scientific computing thus requires familiarity with a range of academic disciplines. The practitioner must, of course, be familiar with the application area of interest, but it is also necessary to understand something of the mathematics and computer science involved.

Whether you are interested in fundamental science, or a technical career in business or industry, it is clear that having expertise in scientific computing would be a valuable, if not essential asset. The question is: how does one acquire such expertise?

This course is one of a suite of MScs in Scientific Computation that are genuinely multidisciplinary in nature. These courses are taught by internationally leading experts in various application areas and in the core areas of mathematics and computing science, fully reflecting the multidisciplinary nature of the subject. The courses have been carefully designed to be accessible to anyone with a good first degree in science or engineering. They are excellent preparation either for research in an area where computational techniques play a significant role, or for a career in business or industry.

Key facts:
- This course is offered in collaboration with the School of Computer Science.
- It is one of a suite of courses focusing on scientific computation.
- The School of Mathematical Sciences is one of the largest and strongest mathematics departments in the UK, with over 50 full-time academic staff.
- In the latest independent Research Assessment Exercise, the school ranked 8th in the UK in terms of research power across the three subject areas within the School of Mathematical Sciences (pure mathematics, applied mathematics, statistics and operational research).

Modules

Advanced Techniques for Differential Equations

Computational Linear Algebra

Operations Research and Modelling

Programming for Scientific Computation

Scientific Computation Dissertation

Simulation for Computer Scientists

Stochastic Financial Modelling

Variational Methods

Vocational Mathematics

Data Mining Techniques and Applications

Mathematical Foundations of Programming

English language requirements for international students

IELTS: 6.0 (with no less than 5.5 in any element)

Further information



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This programme will not have a 2016 intake as the content is being extensively improved. The programme aims to offer a rational, flexibly structured. Read more

NOTE

This programme will not have a 2016 intake as the content is being extensively improved.

OVERVIEW

The programme aims to offer a rational, flexibly structured
and coherent postgraduate study in Automatic Control. While
providing advanced general knowledge in Electronic Engineering, the programme is specifically focussed on nonlinear control principles, measurement instrumentation, simulations and implementation of feedback control.
The programme is designed to provide specific skills for individuals who wish to become a control engineer in manufacturing or research and development in industry sectors, or to pursue a PhD in control engineering.

With a track record of 20 years, the research group Control & Intelligent Control Systems Engineering at the University of Hull has an international reputation for its initiatives in the field of fault diagnostics of dynamic systems. This expertise along with its staff’s teaching experience in control engineering supports the masters programme.

OBJECTIVES

The course will provide students with:
• advanced knowledge of control principles including
multivariable feedback control and nonlinear control
systems,
• essential knowledge of control systems configuration,
algorithm design and evaluation,
• a general knowledge of advanced computer simulation
and measurement instrumentation,
• skills in the software and hardware implementation of
control the latest computer modelling and simulation
techniques,
• research experience in control applications in the
engineering field,
• experience of undertaking a significant relevant
research project

SUBJECTS COVERED

• Multivariable feedback control
• Robotic manipulator control
• Machine vision
• Applied Optoelectronics
• Time Signal Processing and Integrated Circuit Design
• Low Power/Voltage Design and VHDL
• Advanced Digital Systems Design
• Microwave Devices, Techniques and Measurements
• Communication Systems
• Intellectual property rights
• Research skills and project planning

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MSc. This MSc provides advanced training in Electronics, Communications and Computer Engineering. Read more
MSc:

This MSc provides advanced training in Electronics, Communications and Computer Engineering. It will give students a comprehensive coverage of the skills required by an engineer working in instrumentation, electronic systems, wireless and wired telecommunications, computer hardware, and software aspects of computer engineering.

The course provides an excellent basis for engineers wishing to update their knowledge, students who wish to go on to do research, or for first degree students wishing to enhance their training.

Students will develop:
the design, analytical and critical powers in relation to hardware and software aspects of complex electronic systems
the ability to plan and undertake an individual project
interpersonal, communication and professional skills
the ability to communicate ideas effectively in written reports
decision making powers in relation to the specification and solution of embedded system design, system-on-chip (SoC) and electronic engineering problems for appropriate
electronic systems and computer systems

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:
FPGA implementation of the optimized SIFT Algorithm for an image matcher
Zigbee-Based generic wireless data acquisition systems
Digital pulse position modulation for free space optical communication

Please see the school web pages for further details of the PG Dip course.

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

PGDip:

This Postgraduate Diploma provides advanced training in electronics, communications and computer engineering.

The course aims to provide you with a comprehensive coverage of the skills required by an engineer working in instrumentation, electronic systems, wireless and wired telecommunications, computer hardware, and software aspects of computer engineering.

The programme provides an excellent basis for engineers wishing to update their knowledge, or for first degree students wishing to enhance their training.

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This Master degree program is a joint initiative of University of Pisa - Department of Computer Science and Department of Information Engineering, and Sant´Anna School of Advanced Studies - Institute of Communication, Information and Perception Technologies. Read more
This Master degree program is a joint initiative of University of Pisa - Department of Computer Science and Department of Information Engineering, and Sant´Anna School of Advanced Studies - Institute of Communication, Information and Perception Technologies.

Objectives

The two-year Master Program in Computer Science and Networking has been designed to meet the growing demand for an emerging kind of professionals with expertise in both the information and the networking technologies.
This expertise is needed in the design and implementation of both innovative software-hardware distributed infrastructures and service-based distributed applications in several areas of industry, e-business, research, social and citizen services, public administration

Courses and laboratories

The two-year Master degree programme in Computer Science and Networking has a total number of credits (CFU) of 120, where a credit corresponds to 8 hours of lectures/laboratory and 17 hours of personal working activity. The program is organized in around 12 teaching courses (6 or 9 or 12 credits per teaching course), of which 9 major and 3 minor teaching courses, plus the Master Thesis (15 credits).

Major Courses

Algorithm Engineering, Advanced Programming, Distributed Systems Paradigms and Models, Fundamentals of Signals, Systems and Networks, High Performance Computing, Network Configuration and Management, Software Service Engineering, Teletraffic Engineering,

MInor Courses

- software technologies for platforms, systems, models, frameworks, tools, security, and applications in distributed contexts,
- communication technologies for optical and photonic infrastructures, and for network architectures, models, protocols and services,
- applied mathematics for architectures and applications modeling.

The organization of teaching courses and laboratories will allow each student to achieve the most suitable and effective working environment. In order to achieve the described goals for high qualification and working environment, the maximum number of admitted students per year is 42.

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Our Masters in Electrical and Electronic Engineering is a specialist 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 a specialist 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.

See the website http://www.lsbu.ac.uk/courses/course-finder/electrical-electronic-engineering-msc

Modules

- Digital signal processing
This module introduces the theory behind digital signal processing and how DSP can be implemented in real-time. You will gain an understanding of how to program hardware to perform fundamental DSP algorithms such as filtering and spectral analysis. You will gain a fundamental understanding of DSP algorithms and how to implement them in hardware for real-time applications.

- Pattern recognition and machine learning
This module introduces the fundamentals of both statistical learning theory and practical approaches for solving pattern recognition problems. Further, it consolidates lectures with experimental computer-based assignments to inculcate the basics of machine learning and classification. The module covers the fundamentals of pattern recognition and provides the essential background to machine learning and classification.

- Advanced instrumentation and control
This module develops advanced techniques in data acquisition and manipulation required for instrumentation and control applications. Further, it consolidates lectures with experimental computer-based assignments using industry standard hardware and software (NI DAQ and LabView). The module develops your knowledge and experience in data acquisition and virtual instrumentation used in Industry for control purposes.

- Advanced power electronics and renewable energy systems
The material in this module is divided into two parts. The first part covers the analysis and operation of power electronics and machines and their application in the areas of power conversion, power conditioners and electrical machine drives mostly, found on the 'load' side of the electrical power system but sometimes integrated into the supply network. This part will also include elements of computer control systems that are designed to produce non-sinusoidal waveforms and methods of dealing with undesirable harmonics and their effects on the power network. The second part of the module will focus on renewable energy and sustainability. This will include: solar cells, biomass, wind and wave power; intelligent environmental sensing and feedback (in areas of pollution, petroleum, energy consumption, etc.); and renewable design and effectiveness (solar, wind and wave).

- Technology evaluation and commercialization
In this module you will follow a prescribed algorithm in order to evaluate the business opportunity that can be created from a technology's unique advantages. You will be guided towards identifying a technology project idea that you will evaluate for its business potential. To do this you will conduct detailed research and analysis following a prescribed algorithmic model, in order to evaluate the business potential of this technology idea. The outcomes from this will serve as the basis for implementation of the selected technology in the business sense. Thus you will develop the appropriate commercialisation strategy and write the business plan for their high-tech start-up company.

- Technical, research and professional skills
This module provides training for the skills that are necessary for successful completion of the MSc studies in the near future and for professional development in the long-term future. More specifically, the module teaches how to search and gather relevant technical information, how to extract the essence from a piece of technical literature, how to carry out a critical review of a research paper, how to write a feasibility report, how to give presentations and put your thoughts across effectively, and how to manage a project in terms of time and progress in a group project environment. These are designed to enhance the technical and analytical background that is necessary for the respective MSc stream.

- MSc engineering project
This module requires you to undertake a major project in an area that is relevant to their MSc course. You will chose your project and carry it out under the guidance of your supervisor. At the end of the project, you are required to present a dissertation, which forms a major element of the assessment. The dissertation tests your ability to integrate information from various sources, to conduct an in-depth investigation, to critically analyse results and information obtained and to propose solutions. The other element of the assessment includes an oral presentation. The Individual Project carries 60 credits and is a major part of MSc program.

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.

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.

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

Degree information

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

Students undertake modules to the value of 180 credits.

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

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

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

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

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

Careers

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

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

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

Why study this degree at UCL?

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

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

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

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