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Masters Degrees (Algorithm)

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Goal of the pro­gramme. 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 (. Read more

Goal of the pro­gramme

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).

The Master's Programme is offered by the Faculty of Science. Teaching is offered in co-operation with the Faculty of Medicine and the Faculty of Biological and Environmental Sciences. 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

Further information about the studies on the Master's programme website.

Pro­gramme con­tents

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

Algorithmic bioinformatics with the Genome-scale algorithmicsCombinatorial 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 bioinformaticsjointly 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 is offered jointly by the statistics curriculum, the Master´s Programme in Mathematics and Statistics and the research groups Statistical and Translational GeneticsComputational 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 BiomedicumThe 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.



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Algorithm Economy, Data-Driven Decision Making, Industry 4.0, Deep Learning, Artificial Intelligence, Optimization, Data Science, Decision Science - these are just some of the phrases that we read in the headlines with increasing frequency. Read more

Algorithm Economy, Data-Driven Decision Making, Industry 4.0, Deep Learning, Artificial Intelligence, Optimization, Data Science, Decision Science - these are just some of the phrases that we read in the headlines with increasing frequency. The world is on the brink of a new industrial revolution, one in which data, algorithms and analytical thinking will be the key ingredients of value creation; ingredients that global leaders now recognize as their most valuable assets. Enterprises tackling the challenges of tomorrow need to develop new data-centric strategies and leadership, and crucially, must ensure that they attract the most qualified personnel at all levels in the organization; personnel who have the skills to put data-driven approaches into practice and create value for the business from data. Innovation springs from the brightest minds - become a leader of tomorrow by joining our new Master in Management and Engineering in Data and Decision Science. The MME-DDS is positioned at the intersection of Data Science and Operations Research. Our courses bring together expertise from a wide range of fields; machine learning, artificial intelligence, mathematical optimization, heuristic algorithm design and simulation. Electives and domain specializations will give you a competitive advantage in your chosen field. Designed for professionals with a STEM (science, technology, engineering, mathematics) background, the MME-DDS begins with the fundamentals and takes you right up to the cutting-edge of machine learning, artificial intelligence and exact and heuristic optimization. Projects in data science and optimization will give you hands-on experience tackling real-world problems. Electives and specialization will allow you to develop comprehensive domain knowledge and subject matter expertise in engineering and a range of application areas and industry sectors.

Why you should choose the MME-DDS

Enrolling in the MME-DDS will help you to prepare for a career in the data-driven economy. Benefit from the key strengths of the program:

Excellent reputation: RWTH Aachen University enjoys an excellent reputation across the world for cutting-edge research in engineering and technology and is synonymous with German engineering.

Interdisciplinary thinking: Our courses are designed to combine deep knowledge in Data and Decision Science with domain-specific knowledge from engineering and a wide range of application areas and industry sectors. This interdisciplinary profile is highly sought after in global enterprises and SMEs alike.

Networking focus: We place a strong focus on communication amongst participants and lecturers, thus building the foundations of a successful career, enhanced by an international network. This is enhanced by industry internships and the opportunity to study abroad, which are offered to our students as part of the program.

A varied approach to teaching: The program uses a wide range of learning styles and teaching methods. Lectures, case studies, applied projects, group work, topical debates and lab sessions provide a varied and lively learning experience.

Excellent career perspectives: Develop into one of tomorrow’s “unicorns” and become a leader with the skills required for the algorithm economy. At RWTH Aachen University you will gain in-depth theoretical knowledge and develop the tools and the skills to put cutting-edge knowledge into practice.



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Our Advanced Computing MSc programme will provide you with systematic knowledge and experience of the theoretical foundations and practice of computing at an advanced level. Read more

Our Advanced Computing MSc programme will provide you with systematic knowledge and experience of the theoretical foundations and practice of computing at an advanced level. Built around modules such as Algorithm Design and Analysis, Data Structures and their Implementation in C++, and Parallel and Distributed Algorithms, and offering a broad range of optional modules, the course will enhance your abilities to solve advanced computational problems and implement algorithms.

Key benefits

  • Located in central London, giving access to major libraries and leading scientific societies, including the Chartered Institute for IT (BCS), and the Institution of Engineering and Technology (IET).
  • You will learn advanced practical techniques and implementation skills for solving complex computational problems.
  • You will develop critical awareness and appreciation of the changing role of computing in society and motivating you to pursue further professional development and research.
  • Frequent access to speakers of international repute through seminars and external lectures, enabling you to keep abreast of emerging knowledge in advanced computing and related fields.
  • The Department of Informatics has a reputation for delivering research-led teaching and project supervision from leading experts in their field.

Description

Rooted in the renowned research strengths of the Department of Informatics, this programme introduces core topics such as systems programming and algorithms before allowing you to specialise through your choice of modules. The course comprises of optional and required modules, and you will complete the course in one year, studying September to September. You must take modules totalling 180 credits to meet the requirements of the qualification, 60 of which will come from an individual project of around 15,000 words.

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

Teaching

We use lectures, seminars and group tutorials to deliver most of the modules on the programme. You will also be expected to undertake a significant amount of independent study.

Assessment

The primary method of assessment for this course is a combination of written examinations, essays, coursework and individual or group projects and oral presentations. The research project and dissertation will be assessed on one 15,000-word extended piece of writing. 

Career prospects

Our graduates have continued into very successful careers in general software consultancy companies, in specialised software development companies and 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. Some of our graduates have chosen to persue academic and industrial research in software engineering, bio-informatics, algorithms and computer networks.

Sign up for more information. Email now

Have a question about applying to King’s? Email now



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Developed to meet the demand for data science professionals, our postgraduate Data Analytics course enables you to effectively structure, analyse and gain insight from a wide range of complex data across different industries. Read more

Developed to meet the demand for data science professionals, our postgraduate Data Analytics course enables you to effectively structure, analyse and gain insight from a wide range of complex data across different industries.

Designed in close consultation with industry partners including the NHS Business Services Authority, Teradata, BT, SAS, the Pensions Regulator and local Brighton companies, your learning is informed by current business developments through case studies looking at real-world data sets, research questions and scenarios. You have the opportunity to collaborate on projects with our industry partners, and can also use your own data, project ideas and industry links.

Guest lecturers will share their knowledge and expertise with you, such as Tom Khabaza who is a founding chairman of the Society of Data Miners, author of 9 Laws of Data Mining and was involved in designing the course.

You will develop a skill set in specialist data analytics and associated software, quantitative methods and techniques, and business intelligence. Our staff are experts in their field and you have the chance to develop your knowledge in specialist areas where we have ongoing research and expertise, such as sequential forecasting, natural language processing and image processing.

Whether you are a recent graduate or an experienced professional wanting to gain data analysis skills, this course is available on a full or part-time basis to help you manage your studies around other commitments. 

Course structure

The course covers three main areas:

  • data management – structuring and manipulating data for analysis purposes
  • data interpretation – statistical analysis using advanced features of industry-standard software such as SAS, SPSS and R
  • project management – the business-specific and strategic aspects of analytics.

You will learn how to assess project viability, propose sound business cases and strategies for analysis, perform and oversee analysis and manage large data projects successfully as well as developing your critical appraisal and presenting techniques. 

Based at our Moulsecoomb campus, you will have access to computer and research labs equipped with specialist, sophisticated software including SAS, SPSS Statistics and SPSS Modeller. Affordable student licences for home use are also available. 

With a flexible timetable to suit full-time or part-time students and commuters, and lecturers available to support you in your module choices, there are different study routes available to you.

Syllabus

You will study five core modules. One of these involves a major project, potentially in collaboration with industry. You will also choose option modules, subject to availability, allowing you to focus on particular areas of interest.

Core modules

  • Data Management – provides an understanding of contemporary database management systems. Explores a methodology for database design and development, and develops skills in searching, reporting and analysing the data. Topics covered include database implementation and administration, data modelling and business intelligence.
  • Programming for Analytics – provides competencies in computer programming and algorithm design with emphasis on statistical programming and data analysis. The module covers both general issues of algorithm design and data structures and implementation issues in R and SAS.
  • Data Visualisation and Analysis – covers principles of data visualisation and specialised tools for data visualisation and analysis such as SAS Visual Analytics and Qlikview. The module also explores the mathematical and statistical theory behind data analysis.
  • Business Analytics Strategy and Practice – develops analytics-specific project planning concepts within this context, enabling students to design and manage analytics projects and present the business case to senior management.
  • Industry project – substantial, independent project undertaken with the supervision of a member of the teaching team. Projects are normally industry-based using real data sets.

Option modules*

  • Multivariate Analysis and Statistical Modelling – design statistical experiments, analyse multivariate data and apply classical and modern statistical modelling techniques. Enhances skills in the use of specialist software such as R, SPSS or SAS.
  • Data Mining and Knowledge Discovery in Data – find useful and relevant patterns, trends and anomalies in data sets, and summarise them in a form which may be used to support enterprise decisions – one of the great challenges of the information age. Emphasis is on the big, real-world picture rather than inside-the-box systems design engineering details. 
  • Stochastic Methods and Forecasting – an understanding of stochastic models and their applications in a business context. The module also covers forecasting methods with the emphasis on selecting the best forecasting method for a business problem and correct application of that method.
  • Risk Analysis and Retail Finance – introduction to the statistical methods used to estimate risk and reward in retail credit. The focus is on retail finance especially the provision of credit and lending services.
  • Medical Statistics – introduction to the methods originally designed for clinical trials and now being used in other contexts including sociology and marketing research. Topics include assessment of risk factors, comparing treatments and assessing survival data.

*Option modules are indicative and may change, depending on timetabling and staff availability.  

Employability

A wide variety of organisations draw upon data analytics specialists to help produce valuable information for decision-making, for example commodity price forecasting, customer intelligence, clinical trials, R&D and many other areas utilising large amounts of data.

Graduates are able to choose from a range of private, governmental and academic roles, depending on their personal interests. Some of our full-time students find a full-time job and switch to part-time study in the middle of the course.

Graduate destinations include:

  • government bodies such as the Pensions Regulator and local councils
  • transnational corporations such as Capgemini
  • local companies such as iCrossing.


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The Advanced Computing with Management MSc programme is an innovative computer science course, combining high-level programming with an introduction to core management theories and skills in an IT context, making this an ideal study pathway for engineers who already possess a good foundation in programming. Read more

The Advanced Computing with Management MSc programme is an innovative computer science course, combining high-level programming with an introduction to core management theories and skills in an IT context, making this an ideal study pathway for engineers who already possess a good foundation in programming. This course aims to improve your abilities to solve advanced computational problems by gaining knowledge of data structures, design quantitative analysis of algorithms, their applications and implementation.

Key benefits

  • Located in central London, giving access to major libraries and leading scientific societies, including the Chartered Institute for IT (BCS) , and the Institution of Engineering and Technology (IET).
  • You will learn advanced practical techniques and implementation skills for solving complex computational problems.
  • You will develop critical awareness and appreciation of the changing role of computing in society and motivating you to pursue further professional development and research.
  • Frequent access to speakers of international repute through seminars and external lectures, enabling you to keep abreast of emerging knowledge in advanced computing and related fields.
  • The Department of Informatics has a reputation for delivering research-led teaching and project supervision from leading experts in their field.

Description

The Advanced Computing with Management MSc is an innovative course designed to provide you with an in-depth understanding of management roles within the IT industry. The programme will also equip you with essential research, analytical and critical thinking skills.

The course is made up of optional and required modules, completed in one year studying from September to September. You will take modules totalling 180 credits to meet the requirements of the qualification, of which 60 will come from an individual project of around 15000 words.

You will study a range of required modules such as Principles of Management, Algorithm Design and Analysis, and Data Structures and their Implementation in C++ and you will choose further related modules to support your study interests.

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

Teaching

We use lectures, seminars and group tutorials to deliver most of the modules on the programme. You will also be expected to undertake a significant amount of independent study.

Assessment

The primary method of assessment for this course is a combination of written examinations, essays, coursework and individual or group projects and oral presentations. The research project will be assessed on one 15,000-word dissertation.  

Career prospects

Our graduates have continued on to have very successful careers in general software consultancy companies, in specialised software development companies and 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.

While some of our graduates have chosen to go on into academic and industrial research in software engineering, bio-informatics, algorithms and computer networks.

Sign up for more information. Email now

Have a question about applying to King’s? Email now



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Excited by the role of mathematics in securing the modern electronics and communications that we all rely on? This intensive MSc programme explores the mathematics behind secure information and communications systems, in a department that is world renowned for research in the field. Read more

Excited by the role of mathematics in securing the modern electronics and communications that we all rely on? This intensive MSc programme explores the mathematics behind secure information and communications systems, in a department that is world renowned for research in the field.

You will learn to apply advanced mathematical ideas to cryptography, coding theory and information theory, by studying the relevant functions of algebra, number theory and combinatorial complexity theory and algorithms. In the process you will develop a critical appreciation of the challenges that mathematicians face in facilitating secure information transmission, data compression and encryption. You will learn to use advanced cypher systems, correcting codes and modern public key crypto-systems. As part of your studies you will have the opportunity to complete a supervised dissertation in an area of your choice, under the guidance of experts in the field who regularly publish in internationally competitive journals and work closely with partners in industry.

We are a lively, collaborative and supportive community of mathematicians and information security specialists, and thanks to our relatively compact scale we will take the time to get to know you as an individual. You will be assigned a personal advisor to guide you through your studies.

Mathematicians who can push the boundaries and stay ahead when it comes to cryptography and information security are in demand, and the skills you gain will open up a range of career options and provide a solid foundation if you wish to progress to a PhD. These include transferable skills such as familiarity with a computer-based algebra package, experience of carrying out independent research and managing the writing of a dissertation.

  • Learn from internationally renowned mathematicians, cryptographers and communications specialists.
  • Complete a cutting-edge research project under the supervision of cryptography and communications experts.
  • Enjoy the flexibility to tailor your degree to your interests and specialisms.
  • Join a mathematics department that ranks second in the UK for research impact and fourth for world leading or internationally excellent research output (Research Excellence Framework 2014).
  • Feel at home in a friendly department where you will be known as an individual.

Course structure

Core modules

  • Main Project
  • Advanced Cipher Systems
  • Channels
  • Theory of Error-Correcting Codes
  • Public Key Cryptography

Optional modules

In addition to these mandatory course units there are a number of optional course units available during your degree studies. The following is a selection of optional course units that are likely to be available. Please note that although the College will keep changes to a minimum, new units may be offered or existing units may be withdrawn, for example, in response to a change in staff. Applicants will be informed if any significant changes need to be made.

  • Applications of Field Theory
  • Quantum Information and Coding
  • Principles of Algorithm Design
  • Advanced Financial Mathematics
  • Combinatorics
  • Computational Number Theory
  • Complexity Theory
  • Inference
  • Topology
  • Applied Probability

Teaching & assessment

You will initially choose 8 courses from the list of available options, of which you specify 6 courses during the second term that will count towards your final award. You will also complete a core research project under the supervision of one of our academic staff.There is a strong focus on small group teaching throughout the programme.

Assessment is carried out through a variety of methods, including coursework, examinations and the main project. End-of-year examinations in May or June will count for 66.7% of your final award, while the dissertation will make up the remaining 33.3% and has to be submitted by September.

Your future career

By the end of this programme you will have an advanced knowledge and understanding of all the key mathematical principles and applications that underpin modern cryptography and communications. You will have advanced skills in coding, algebra and number theory, and be able to synthesise and interpret information from multiple sources with insight and critical awareness. You will have learnt to formulate problems clearly, to undertake independent research and to express your technical work and conclusions clearly in writing. You will also have valuable transferable skills such as advanced numeracy and IT skills, time management, adaptability and self-motivation.

Graduates from this programme have gone on to carry out cutting-edge research in the fields of communication theory and cryptography, as well as to successful careers in industries such as: information security, IT consultancy, banking and finance, higher education and telecommunications. Our mathematics postgraduates have taken up roles such as: 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.

The campus Careers team will be on hand to offer advice and guidance on your chosen career. The University of London Careers Advisory Service runs regular, tailored sessions for mathematics students, on finding summer internships or vacation employment and getting into employment.

  • Open doors to a range of exciting opportunities in academic research or professional employment.
  • Our strong ties with industry mean we understand the needs of employers and we have a strong track record of helping graduates into successful, high-level careers.
  • 90% of our graduates are in work or undertaking further study within six months of leaving (Unistats 2015).


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“There is no branch of mathematics, however abstract, which may not someday be applied to phenomena of the real world.” –. Nikolai Ivanovich Lobachevsky. Read more

“There is no branch of mathematics, however abstract, which may not someday be applied to phenomena of the real world.” – Nikolai Ivanovich Lobachevsky

If you're looking to take your undergraduate mathematics experience to new levels and develop advanced research skills, this intensive programme covers the wide spectrum of discrete mathematics, applied mathematics and statistics, and addresses some of the key quantifiable challenges and opportunities in the world around us. An interdisciplinary subject by nature, we will help you to apply mathematical concepts and methods to the ever-changing worlds of science, engineering, business, digital technology and industry, and particularly to communication theory, mathematical physics and financial mathematics, where some of our key research interests lie.

The skills you gain will open up a range of career options and provide a solid foundation if you wish to progress to a PhD. You will be guided by renowned specialists in the field who publish in internationally competitive journals and work closely with partners in industry.

Join our friendly and inspiring department and you will benefit from a thoroughly supportive learning environment, with generous staff office hours and a dedicated personal advisor to help you with any queries and guide you through your degree. Our graduates are in demand for their skills in research, numeracy, data handling and analysis, logical thinking and creative problem solving.

  • Apply your mathematics to real-world situations and gain the skills to work at a high level in industry, business or research.
  • Learn from internationally renowned mathematicians. We rank second in the UK for our research impact and fourth for world leading or internationally excellent research output (Research Excellence Framework 2014).
  • Feel at home in a friendly department where you will be known as an individual.

Course structure

Core modules

  • Main Project: You will carry out a detailed study into a topic of your choosing in mathematics, analysing information from a range of sources. You will submit a written report of between 8,000 and 16,000 words in length.

Optional modules

In addition to these mandatory course units there are a number of optional course units available during your degree studies. The following is a selection of optional course units that are likely to be available. Please note that although the College will keep changes to a minimum, new units may be offered or existing units may be withdrawn, for example, in response to a change in staff. Applicants will be informed if any significant changes need to be made.

  • Theory of Error-Correcting Codes
  • Channels
  • Advanced Cipher Systems
  • Public Key Cryptography
  • Applications of Field Theory
  • Quantum Information and Coding
  • Principles of Algorithm Design
  • Advanced Financial Mathematics
  • Combinatorics
  • Computational Number Theory
  • Applied Probability
  • Inference
  • Topology

Teaching & assessment

You will initially choose eight modules from the list of available options, of which you specify modules during the second term that will count towards your final award. You will also complete a core research project under the supervision of one of our academic staff. There is a strong focus on small group teaching throughout the programme.

Assessment is carried out through a variety of methods, including coursework, examinations and the main project. End-of-year examinations in May or June will count for 66.7% of your final award, while the dissertation will make up the remaining 33.3%.

Your future career

By the end of this programme you will have completed a major research project and acquired an advanced knowledge and understanding of: the role and limitations of mathematics in solving problems that arise in real-world scenarios. You will also have impressive skills in selected areas of mathematics and their applications, and the ability to synthesise and interpret information from multiple sources with insight and critical awareness. We will teach you to formulate problems clearly and express your technical work and conclusions clearly in writing, and you will develop valuable transferable skills such as time management, adaptability and self-motivation.

Our graduates have gone on to carry out cutting-edge research in the fields of communication theory and cryptography, as well as successful careers in industries such as: information security, IT consultancy, banking and finance, higher education and telecommunication. They have taken up roles such as: 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.

You will have a dedicated personal adviser to guide you through your studies and advise you on postgraduate opportunities, and the campus Careers team will be on hand to offer advice and guidance on your chosen career. The University of London Careers Advisory Service offers regular, tailored sessions for Mathematics students, on finding summer internships or vacation employment and getting into employment.

  • Open doors to a range of exciting opportunities in advanced research, science and industry.
  • 90% of our graduates are in work or undertaking further study within six months of leaving (Unistats 2015).
  • Our strong ties with industry mean we understand the needs of employers.
  • Take advantage of our summer work placement scheme and fine-tune your CV before you enter your final year.
  • Benefit from a personal advisor who will guide you through your studies and future options.


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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
  • Microsystems Engineering
  • Neuroscience
  • 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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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. 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 60 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 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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This course provides you with comprehensive training in the essential elements of information engineering and communications. Module options are topical and relevant, encompassing the design of application-specific integrated circuits, micro-electromechanical systems and optical engineering. Read more
This course provides you with comprehensive training in the essential elements of information engineering and communications. Module options are topical and relevant, encompassing the design of application-specific integrated circuits, micro-electromechanical systems and optical engineering.

You’ll also have the opportunity to tap into the world of Computer Science and explore ‘big data’, covering themes such as digital multimedia storage and communications technologies, data analytics and data mining in terms of algorithms, and goals in real-world problems. You’ll also pick up transferable skills for any future study or career, such as project planning and management, ethics, health and safety, report writing, library skills and career management.

Our recent graduates now occupy positions in industries ranging from core network provision through to logistics and software support, in addition to opportunities in data communication equipment and services.

Course description

The MSc degree (totalling 180 credits) comprises eight taught modules (15 credits each), five core modules and three optional modules (see below), along with a research project worth 60 credits (see below).

Core modules

-Advanced Wireless Systems and Networks
-Information Theory and Coding
-Antenna, Propagation and Wireless Communications Theory
-Optical Communication Systems
-Signal & Image Processing

Optional modules

ASICs, MEMS and Smart Devices
Optical Engineering
Data Mining (from Computer Science)
Foundations of Data Analytics (from Computer Science)
Multimedia Processing, Communications and Storage (from Computer Science)

Individual research project

The individual research project is an in-depth experimental, theoretical or computational investigation of a topic chosen by you in conjunction with your academic supervisor. Typical project titles include:
-Network coding for underwater communications.
-Nanoscale communication networks.
-Forward Error Correction for Spectrally Sliced Transmission.
-Routing Algorithm Design for Mobile Ad Hoc Networks.
-Logical Stochastic Resonance.
-Design of Radio Devices using Metamaterials.
-Nonlinear Effects in Optical Fibre Transmission.

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With the launch of 4G wireless networks (LTE), industry vendors are competing to recruit graduates with unique combination of skills and knowledge in both wireless and broadband networking fields. Read more
With the launch of 4G wireless networks (LTE), industry vendors are competing to recruit graduates with unique combination of skills and knowledge in both wireless and broadband networking fields. This course offers an integrated approach to transmission technologies, signal processing techniques, broadband network design, wireless networking techniques and modelling simulation skills.

The unique features of this course are the integration of latest wireless communications and broadband networking engineering which are at the forefront of modern telecommunication systems in the industry today.

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.

As a student here you'll benefit from well-equipped telecommunications lab and Cisco equipment.

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

Modules

- 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 course 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.

- Computer network design
This module provides a broad understanding of the principles of computer networks and approaches of network design. It starts from standard layered protocol architecture and each layer of the TCP/IP model. Then it will focus on a top-down approach for designing computer networks for an enterprise.

- Wireless communication and satellite systems
This module provides understanding of main aspects of wireless communication technologies, various radio channel models, wireless communication networks and satellite communication systems. Particular emphasis will be given to current wireless technologies and architectures, design approaches and applications.

- Technology evaluation and commercialisation
In this module you'll 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'll 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'll develop the appropriate commercialisation strategy and write the business plan for your high-tech start-up company.

- Optical and microwave communications
This module provides a comprehensive approach to teach the system aspects of optical and microwave communications, with the emphasis on applications to Fibre-to-the Home (FTTH)/Fibre-to-the Business (FTTB) or Fibre-to-the Curb (FTTC), radio over fibre (RoF), optical-wireless integration, high-capacity photonic switching networks, wired and wireless broadband access systems, and high-speed solutions to last-mile access, respectively.

- Smart receivers and transmission techniques
This module provides a further in-depth study of some advanced transmission and receiver processing techniques in wireless communication systems. The module focuses on various current topics such as evolution and challenges in wireless and mobile technologies, smart transceivers, processing, coding and possible future evolutions in mobile communication systems. This module also aims to provide you with in-depth understanding and detailed learning objectives related the current mobile wireless industry trends and standards for key design considerations in related wireless products.

- Final project
This module requires you to undertake a major project in an area that is relevant to your course. You'll chose your projects and carry it out under the guidance of their 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 the 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

Engineers who keep abreast of new technologies in telecommunications, wireless and broadband networking are increasingly in demand.

There are diverse employment opportunities in this expanding field. Graduates could work for an equipment manufacturer, network infrastructure provider or a service provider, carrying out research, or working on the design and development projects, or production of data networks, broadband networking, optical fibre and microwave communications, wireless and mobile communications, cellular mobile networks or satellite systems. You could also pursue PhD studies after completing the course.

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 of Engineering 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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The field of computer science has produced some of the most significant advances in modern technology over the last three decades and radically transformed business and industry practices on a global scale. Read more
The field of computer science has produced some of the most significant advances in modern technology over the last three decades and radically transformed business and industry practices on a global scale. There is a profound need for postgraduate-level practitioners in this discipline.

Why Study Advanced Computer Science with us?

Taught at our Thornton Science Park near Chester, this course focuses on the Department of Computer Science’s strengths, providing a cutting-edge curriculum in medical graphics, data visualisation, cybersecurity, discrete optimisation and image processing, in addition to core computer science topics such as algorithm design.

There is also a monthly seminar programme in which leading experts present recent findings and introduce contemporary developments in the above and other areas.

The Department’s commitment to part-time, evening delivery (as an additional alternative to full-time delivery) is particularly attractive to those in employment wishing to gain a postgraduate qualification. This provision is rare among competing institutions and one that has been successfully delivered at Chester for many years.

What will I learn?

The course has a core theme addressing advanced issues in software and algorithmic development, which will equip you to deal with complex problems using a wide range of contemporary techniques. Additionally, the development of a rigorous approach to research and original enquiry will be fostered in our Research Methods and Research Dissertation modules.

Optional modules cover a range of applied topics where the Department has expertise, including data visualisation, virtual reality, computer vision and cybersecurity.

How will I be taught?

The course will be delivered at our modern facilities at Thornton Science Park, which include a VR laboratory, high performance computing facility and cybersecurity laboratories.

You will be taught using a mixture of lectures, workshops, seminars and case studies.
There are 7½ contact hours per week, and you will be expected to undertake 30 hours of private study per week.

How will I be assessed?

Assessment takes place using roughly 30% exams and 70% coursework, although the precise ratio depends on module choices.

Postgraduate Visit Opportunities

If you are interested in this courses we have a number of opportunities to visit us and our campuses. To find out more about these options and to book a visit, please go to: https://www1.chester.ac.uk/study/postgraduate/postgraduate-visit-opportunities

Request a Prospectus

If you would like to know more about the University please request a prospectus at: http://prospectus.chester.ac.uk/form.php

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