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Masters Degrees (Discrete Mathematics)

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Mathematics underlies some vital situations in practical life. Game theory, with roots in mathematics, statistics and economics, is routinely applied to understanding and predicting human behaviour. Read more
Mathematics underlies some vital situations in practical life.

Game theory, with roots in mathematics, statistics and economics, is routinely applied to understanding and predicting human behaviour. Problems of protection of digital information against piracy are closely related to aspects of set systems. And the RSA cryptosystem, used on computers all over the world, depends on classical results of number theory.

Our MSc Mathematics covers many aspects of discrete mathematics and their potential use in practice, and provides you with options in:
-Optimisation
-Machine learning
-Data mining
-Statistics

Our interdisciplinary research recognises that mathematics, including what can be very abstract mathematics, is an essential part of research in many other disciplines.

Our Department of Mathematical Sciences has an international reputation in many areas including semi-group theory, optimisation, probability, applied statistics, bioinformatics and mathematical biology.

This course can also be studied to a PGDip level - for more information, please view this web-page: http://www.essex.ac.uk/courses/details.aspx?mastercourse=PG00538&subgroup=2

Our expert staff

Our Department of Mathematical Sciences is a small but influential department, so our students and staff know each other personally. You never need an appointment to see your tutors and supervisors, just knock on our office doors – we are one of the few places to have an open-door policy, and no issue is too big or small.

Our staff have published several well-regarded text books and are world leaders in their individual specialisms, with their papers appearing in learned journals like Communications in Algebra, Studia Logica, International Journal of Algebra and Computation, SIAM Journal in Optimization, IEEE Evolutionary Computation, Computers and Operations Research, Ecology, Journal of Mathematical Biology, and Journal of Statistical Applications in Genetics and Molecular Biology.

Specialist facilities

-Unique to Essex is our renowned Maths Support Centre, which offers help to students, staff and local businesses on a range of mathematical problems. Throughout term-time, we can chat through mathematical problems either on a one-to-one or small group basis
-We have our own computer labs for the exclusive use of students in the Department of Mathematical Sciences – in addition to your core maths modules, you gain computing knowledge of software including Matlab and Maple
-We host regular events and seminars throughout the year
-Our students run a lively Mathematics Society, an active and social group where you can explore your interest in your subject with other students

Your future

Key employability skills you gain from this course include analytic reasoning, problem solving, techniques of discrete mathematics and an understanding of application areas of these techniques, algorithm design and implementation, and data analysis.

Our graduates are highly sought after by a range of employers and find employment in financial services, scientific computation, decision making support and government, risk assessment, statistics, education and other sectors.

We also offer supervision for PhD, MPhil and MSc by Dissertation. We have an international reputation in many areas such as semi-group theory, optimisation, probability, applied statistics, bioinformatics and mathematical biology, and our staff are strongly committed to research and to the promotion of graduate activities.

We additionally work with our Employability and Careers Centre to help you find out about further work experience, internships, placements, and voluntary opportunities.

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The ideas of applied mathematics pervade several applications in a variety of businesses and industries as well as government. Sophisticated mathematical tools are increasingly used to develop new models, modify existing ones, and analyze system performance. Read more

Program overview

The ideas of applied mathematics pervade several applications in a variety of businesses and industries as well as government. Sophisticated mathematical tools are increasingly used to develop new models, modify existing ones, and analyze system performance. This includes applications of mathematics to problems in management science, biology, portfolio planning, facilities planning, control of dynamic systems, and design of composite materials. The goal is to find computable solutions to real-world problems arising from these types of situations.

The master of science degree in applied and computational mathematics provides students with the capability to apply mathematical models and methods to study various problems that arise in industry and business, with an emphasis on developing computable solutions that can be implemented. The program offers options in discrete mathematics, dynamical systems, and scientific computing. Students complete a thesis, which includes the presentation of original ideas and solutions to a specific mathematical problem. The proposal for the thesis work and the results must be presented and defended before the advisory committee.

Curriculum

Several options available for course sequence:
-Discrete mathematics option
-Dynamical systems option
-Scientific computing option

See website for individual module details.

Other entry requirements

-Submit official transcripts (in English) of all previously completed undergraduate and graduate course work.
-Submit a personal statement of educational objectives.
-Have an undergraduate cumulative GPA of 3.0 or higher.
-Submit two letters of recommendation, and complete a graduate application.
-International applicants whose primary language is not English must submit scores from the Test of English as a Foreign Language (TOEFL). A minimum score of 550 (paper-based) or 79-80 (Internet-based) is required. International English Language Testing System (IELTS) scores are accepted in place of the TOEFL exam. Minimum scores vary; however, the absolute minimum score required for unconditional acceptance is 6.5. For additional information about the IELTS, please visit http://www.ielts.org. Those who cannot take the TOEFL will be required to take the Michigan Test of English Proficiency at RIT and obtain a score of 80 or higher.
-Although Graduate Record Examination (GRE) scores are not required, submitting them may enhance a candidate's acceptance into the program.
-A student may also be granted conditional admission and be required to complete bridge courses selected from among RIT’s existing undergraduate courses, as prescribed by the student’s adviser. Until these requirements are met, the candidate is considered a nonmatriculated student. The graduate program director evaluates the student’s qualifications to determine eligibility for conditional and provisional admission.

Additional information

Student’s advisory committee:
Upon admission to the program, the student chooses an adviser and forms an advisory committee. This committee oversees the academic aspects of the student’s program, including the selection of a concentration and appropriate courses to fulfill the program’s requirements.

Cooperative education:
Cooperative education enables students to alternate periods of study on campus with periods of full-time, paid professional employment. Students may pursue a co-op position after their first semester. Co-op is optional for this program.

Part-time study:
The program is ideal for practicing professionals who are interested in applying mathematical methods in their work and enhancing their career options. Most courses are scheduled in the late afternoon or early evening. The program may normally be completed in two years of part-time study.

Nonmatriculated students:
A student with a bachelor’s degree from an approved undergraduate institution, and with the background necessary for specific courses, may take graduate courses as a nonmatriculated student with the permission of the graduate program director and the course instructor. Courses taken for credit may be applied toward the master’s degree if the student is formally admitted to the program at a later date. However, the number of credit hours that may be transferred into the program from courses taken at RIT is limited for nonmatriculated students.

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Data encryption, risk management in finance and insurance and mathematical imaging – mathematicians use analytic and computer-assisted techniques to understand the increasing complexity in natural sciences, life sciences, economics and engineering. Read more

Data encryption, risk management in finance and insurance and mathematical imaging – mathematicians use analytic and computer-assisted techniques to understand the increasing complexity in natural sciences, life sciences, economics and engineering.

Josef Strini, master's degree student in Mathematics:

"Whether we’re solving sample exercises or discussing the most recent lectures, there are always possibilities for exchanging information with the students and lecturers in my programme. I recommend my programme to all those who are interested in mathematical relationships, are prepared to critically examine these and have the drive and patience to ensure their accuracy."

Content

In compulsory and advanced courses, you develop mathematical knowledge in the following areas:

  • Analysis
  • Algebra
  • Stochastics
  • Numerical mathematics
  • Discrete mathematics

You choose from one of the following specialisations:

  • Applied mathematics
  • Discrete mathematics
  • Financial and actuarial mathematics
  • Statistics and operations research
  • Mathematical engineering

For the individual courses, please see the semester plan.

Career Options

Mathematicians work in areas such as industry, commerce and science.

  • They apply mathematical methods in industry, technology and the natural sciences.
  • They use deterministic and stochastic models in commerce, administration, finance and insurance.
  • They tackle questions of data security and communication technology in theory and practice.
  • They develop methods without which many devices and technologies of modern day life would not exist - for example, imaging processes in medicine and technology, communication and security in data transfer, risk management for banks and insurance companies, and computer-aided processes in natural sciences and technology.


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This Masters degree provides you with knowledge of advanced finance concepts, whilst developing your quantitative, mathematical and research skills. Read more

This Masters degree provides you with knowledge of advanced finance concepts, whilst developing your quantitative, mathematical and research skills.

Taught by experienced academics based in both Leeds University Business School and the School of Mathematics, you’ll cover key topics including financial derivative pricing, discrete and continuous time models, risk management and portfolio optimisation, as well as statistical methods for finance.

You will be equipped with a rare combination of mathematical skills and the latest business finance knowledge, which is highly sought after in the financial sector by banks, investment and consultancy companies. It’s also excellent preparation if you’re interested in pursuing further academic research.

This course is ideal if you’ve previously studied finance, economics, mathematics, physics or computing, and are interested in applying your skills to financial markets.

Academic excellence

As a student, you will be able to access the knowledge of our advanced specialist research units, which also have strong links with leading institutions in the US, Europe and Asia. These include the Centre for Advanced Study in Finance (CASIF), the Institute of Banking and Investment (IBI) and the Credit Management Research Centre (CMRC).

This research makes an important contribution to your learning on the MSc Financial Mathematics; you will benefit from a curriculum that is informed by the latest knowledge and critical thinking.

You will also benefit from our strong relationships with the finance, credit and accounting professions. This provides a connection to the latest practitioner and policy developments, giving you a masters degree that is relevant to the contemporary environment.

Course content

In your first semester you’ll develop a broad understanding of corporate finance and how financial theory relates to practice in business and financial markets. This will put your mathematical studies into context while you develop your skills in applied statistics and probability, optimisation methods and discrete time finance.

You’ll build on these skills in topics such as continuous time finance, risk management and computational methods. You’ll also gain specialist knowledge in topics that suit your career ambitions such as risk and insurance, actuarial science and behavioural finance.

The programme will improve your research skills and allow you to study different research methodologies, including those employed by our own leading academics. This will prepare you for your dissertation – an independent research project on a topic of your choice that you’ll submit by the end of the year.

Course structure

Compulsory modules

  • Corporate Finance 15 credits
  • Dissertation in Financial Mathematics 30 credits
  • Applied Statistics and Probability 15 credits
  • Discrete Time Finance 15 credits
  • Continuous Time Finance 15 credits
  • Risk Management 15 credits
  • Computations in Finance 15 credits
  • Optimisation Methods for Finance 15 credits

Optional modules

You'll also take two optional modules.

  • Security Investment Analysis 15 credits
  • Portfolio Risk Management 15 credits
  • Behavioural Finance 15 credits
  • Financial Derivatives 15 credits
  • International Investment 15 credits
  • Models in Actuarial Science 15 credits

For more information on typical modules, read Financial Mathematics MSc in the course catalogue

Learning and teaching

We use a variety of teaching and learning methods to help you make the most of your studies. These will include lectures, seminars, workshops, online learning and tutorials. Independent study is also vital for this course allowing you to prepare for taught classes and sharpen your own research and critical skills.

In addition to the assessed modules and research dissertation, you benefit from professional training activities and employability workshops. Thanks to our links with major companies across the business world, you can also gain a practical understanding of key issues.

Recent activities have included CV building and interview sessions, professional risk management workshops and commercial awareness events. For example, students have developed their knowledge of financial markets through a one-week trading simulation. Read more about professional development activities for postgraduate finance students.

Assessment

Assessment methods emphasise not just knowledge, but essential skills development too. They include formal exams, group projects, reports, computer simulation exercises, essays and written assignments, group and individual presentations.

This diversity enables you to develop a broad range of skills as preparation for professional life.

Career opportunities

You have various opportunities open to you as a Financial Mathematics graduate, including: quantitative analysis, risk management, investment banking, financial consultancy, insurance, accounting and academia.

Previous graduates have gone on to secure employment with Allianz (London), AstraZeneca, Barclays, Cathay Life Insurance, CITIC Group, Commerzbank, Deloitte, First Direct, Gaz de France, HSBC, KPMG, Moody’s, PricewaterhouseCoopers, Royal Bank of Scotland, RSA and UK Government Actuary’s Department.

Careers support

We help you to achieve your career ambitions by providing professional development support and training as part of the course. You benefit from the support of a professional development tutor, who will work with you to develop the important professional skills that employers value.

Read more about our careers and professional development support.

The University of Leeds Careers Centre also provides a range of help and advice to help you plan your career and make well-informed decisions along the way, even after you graduate. Find out more at the Careers website



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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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Your programme of study. Many organisations particularly in the financial sector require quite complex financial transactions to be completed within their systems and databases internally and externally in order to provide the most up to date financial information to customers. Read more

Your programme of study

Many organisations particularly in the financial sector require quite complex financial transactions to be completed within their systems and databases internally and externally in order to provide the most up to date financial information to customers. Other organisations particularly within trading and investment areas, currencies and international organisations rely on modelling and scenarios to ensure their business models survive change. There are a lot of businesses and applications that require somebody with Financial Mathematics to set up systems which allow internal and external customers to see exact information whilst calculations go on behind the scenes. The insurance, pensions and domestic energy industries are good examples of business which requires a specific ability to provide advanced methods of calculation.

The programme gives you a rigorous method of acquiring vital skills which financial industries are looking for. You learn financial programme and work with big data sets used in the above industries, banking and many other industries. There is also a new industry which relies on these skills to programme IOT applications and devices which are used to similarly calculate within financial and statistical markets.

Courses listed for the programme

Semester 1

Discrete Time Modules

Economics Theory for Finance

Economics Theory and Data Analysis for Finance

Mathematics for Finance

Semester 2

Continuous Time Models

Time Series

Semester 3

Dissertation

Find out more detail by visiting the programme web page

https://www.abdn.ac.uk/study/postgraduate-taught/degree-programmes/920/financial-mathematics/

Why study at Aberdeen?

• You get access to Thomson Reuters Eikon trading floor to integrate study with real time trading

• We are supported by strong research collaborations with the Institute of Pure and Applied Mathematics

• You are also supported by our Business School

• Skills which are essential to financial economists in private and public sector are taught to develop rigour and confidence

Where you study

• University of Aberdeen

• Full time

International Student Fees 2017/2018

Find out about fees:

https://www.abdn.ac.uk/study/international/tuition-fees-and-living-costs-287.php

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

Scholarships

View all funding options on our funding database via the programme page

https://www.abdn.ac.uk/study/postgraduate-taught/finance-funding-1599.php

https://www.abdn.ac.uk/funding/

Living in Aberdeen

Find out more about:

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

Find out more about living in Aberdeen:

https://abdn.ac.uk/study/student-life

Living costs

https://www.abdn.ac.uk/study/international/finance.php



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This masters programme covers the advanced mathematics that has revolutionised finance since the works of Black, Scholes and Merton in the early seventies. Read more
This masters programme covers the advanced mathematics that has revolutionised finance since the works of Black, Scholes and Merton in the early seventies. This programme is aimed at those students who are passionate about mathematics and driven to make a career amongst the many and varied financial institutions throughout the world.

The programme, which is part of the Maxwell Institute for Mathematical Sciences, the joint research institute of mathematical sciences at the University of Edinburgh and Heriot-Watt University, provides an intensive training in the mathematical ideas and tools vital to the finance industry. By developing essential new mathematical concepts, especially in stochastic calculus, and placing the mathematics in the contexts of financial markets, derivative pricing and credit risk, the programme equips students for a range of exciting and potentially lucrative career opportunities.

The programme is delivered jointly between Heriot-Watt University and the University of Edinburgh. This means you will be enrolled as a student at both univerities and benefit from access to all the services and facilities each university has to offer.

Teaching is delivered by renowned academics from both Heriot-Watt and the University of Edinburgh - some classes will therefore take place at Heriot-Watt's campus and others at the University of Edinburgh campus. Successful students will graduate with a degree awarded jointly by Heriot-Watt and the University of Edinburgh and both names will appear on the graduation certificate.

Programme content

Core courses

Derivatives Markets
Derivative Pricing and Financial Modelling
Financial Markets
Discrete-Time Finance
Stochastic Analysis in finance
Credit Risk Modelling
Special Topics, including industry lead projects

Options

Statistical Methods
Financial Econometrics
Time Series Analysis
Modern Portfolio Theory
Optimisation Methods in Finance
Numerical Methods for PDEs
Simulation in Finance
Deterministic Optimisation Methods in Finance

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The MSc Applicable Mathematics is an innovative programme, drawing together traditional and modern mathematical techniques in a variety of social science contexts. Read more

About the MSc programme

The MSc Applicable Mathematics is an innovative programme, drawing together traditional and modern mathematical techniques in a variety of social science contexts. It is designed both for mathematicians who wish to make themselves more marketable by adding some social science aspects to their knowledge and skills base, and for non-mathematicians with strong quantitative backgrounds who wish to add to and improve their understanding of the mathematics behind much of social science.

The programme will provide you with an increased knowledge of mathematics, particularly in algorithms, game theory, discrete mathematics, probability and stochastics, and optimisation, in addition to training in appropriate computational methods. Reflecting the world's dependence on computation, students will learn the programming language Java, and how to use it to apply their knowledge to real-world problems.

The skills and knowledge gained over the programme will open up a wide range of potential careers, including finance, business, software development, and industry. It will also provide a solid base for further studies at research level.

Graduate destinations

This programme is ideal preparation for a range of careers in industry, finance, government and research. Graduates of the programme have found employment in companies such as Amazon; BlackRock; Credit Suisse; Facebook; Goldman Sachs; Google; KPMG; National Grid and RBS.

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If you are interested in the possibility of a research degree (PhD or Research Masters) in the School of Mathematical Sciences, we encourage you to become familiar with the range of research activity and expertise in the School. Read more
If you are interested in the possibility of a research degree (PhD or Research Masters) in the School of Mathematical Sciences, we encourage you to become familiar with the range of research activity and expertise in the School. In particular, we would encourage you to approach or contact members of the academic staff whose research area may be of particular interest.

The research of the School covers a wide range of areas including:

Analysis (Infinite-dimensional analysis, Functional Analysis, Potential Theory)
Algebra (Matrix Theory, K-theory, Quadratic and Hermitian Forms)
Discrete Mathematics (Coding, Cryptography, Number Theory)
Applied Mathematics (Fluid Dynamics, Computational Science, Meteorology, Biomathematics, Information Theory)
Theoretical Physics (Astrophysics, General Relativity, Quantum Gravity, Statistical Mechanics, Quantum Field Theory)
Statistics (Bayesian Statistics, Pharmaceutical, Medical and Educational Statistics, Environmental and ecological modelling, Epidemiology, Econometrics).

Please see our School Website for more details:
http://www.ucd.ie/mathstat

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The MSc in Bioinformatics and Computational Biology at UCC is a one-year taught masters course commencing in September. Bioinformatics is a fast-growing field at the intersection of biology, mathematics and computer science. Read more
The MSc in Bioinformatics and Computational Biology at UCC is a one-year taught masters course commencing in September. Bioinformatics is a fast-growing field at the intersection of biology, mathematics and computer science. It seeks to create, advance and apply computer/software-based solutions to solve formal and practical problems arising from the management and analysis of very large biological data sets. Applications include genome sequence analysis such as the human genome, the human microbiome, analysis of genetic variation within populations and analysis of gene expression patterns.

As part of the MSc course, you will carry out a three month research project in a research group in UCC or in an external university, research institute or industry. The programming and data handling skills that you will develop, along with your exposure to an interdisciplinary research environment, will be very attractive to employers. Graduates from the MSc will have a variety of career options including working in a research group in a university or research institute, industrial research, or pursuing a PhD.

Visit the website: http://www.ucc.ie/en/ckr33/

Course Detail

This MSc course will provide theoretical education along with practical training to students who already have a BSc in a biological/life science, computer science, mathematics, statistics, engineering or a related degree.

The course has four different streams for biology, mathematics, statistics and computer science graduates. Graduates of related disciplines, such as engineering, physics, medicine, will be enrolled in the most appropriate stream. This allows graduates from different backgrounds to increase their knowledge and skills in areas in which they have not previously studied, with particular emphasis on hands-on expertise relevant to bioinformatics:

- Data analysis: basic statistical concepts, probability, multivariate analysis methods
- Programming/computing: hands-on Linux skills, basic computing skills and databases, computer system organisation, analysis of simple data structures and algorithms, programming concepts and practice, web applications programming
- Bioinformatics: homology searches, sequence alignment, motifs, phylogenetics, protein folding and structure prediction
- Systems biology: genome sequencing projects and genome analysis, functional genomics, metabolome modelling, regulatory networks, interactome, enzymes and pathways
- Mathematical modelling and simulation: use of discrete mathematics for bioinformatics such as graphs and trees, simulation of biosystems
- Research skills: individual research project, involving a placement within the university or in external research institutes, universities or industry.

Format

Full-time students must complete 12 taught modules and undertake a research project. Part-time students complete about six taught modules in each academic year and undertake the project in the second academic year. Each taught module consists of approximately 20 one-hour lectures (roughly two lectures per week over one academic term), as well as approximately 10 hours of practicals or tutorials (roughly one one-hour practical or tutorial per week over one academic term), although the exact amount of lectures, practicals and tutorials varies between individual modules.

Assessment

There are exams for most of the taught modules in May of each of the two academic years, while certain modules may also have a continuous assessment element. The research project starts in June and finishes towards the end of September. Part-time students will carry out their research project during the summer of their second academic year.

Careers

Graduates of this course offer a unique set of interdisciplinary skills making them highly attractive to employers at universities, research centres and in industry. Many research institutes have dedicated bioinformatics groups, while many 'wet biology' research groups employ bioinformaticians to help with data analyses and other bioinformatics problems. Industries employing bioinformaticians include the pharmaceutical industry, agricultural and biotechnology companies. For biology graduates returning to 'wet lab' biology after completing the MSc course, your newly acquired skills will be extremely useful. Non-biology graduates seeking non-biology positions will also find that having acquired interdisciplinary skills is of great benefit in getting a job.

How to apply: http://www.ucc.ie/en/study/postgrad/how/

Funding and Scholarships

Information regarding funding and available scholarships can be found here: https://www.ucc.ie/en/cblgradschool/current/fundingandfinance/fundingscholarships/

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Research in Computer Science at York is carried out at the frontiers of knowledge in the discipline. This course gives you the chance to study a range of advanced topics in Computer Science, taught by researchers active in that area. Read more
Research in Computer Science at York is carried out at the frontiers of knowledge in the discipline. This course gives you the chance to study a range of advanced topics in Computer Science, taught by researchers active in that area. This means you will be learning current research results, keeping you at the forefront of these areas. You will also learn a range of theories, principles and practical methods.

The MSc in Advanced Computer Science is a full time, one year taught course, intended for students who already have a good first degree in Computer Science, and would like to develop a level of understanding and technical skill at the leading edge of Computer Science.

You can choose modules on a range of topics, including Cryptography, Functional Programming, Interactive Technologies, Natural Language Processing, Quantum Computation and Model-Driven Engineering.

Course aims
You will gain an in-depth knowledge of topics on the frontiers of Computer Science in order to engage in research or development and application of leading-edge research findings.

By undertaking an individual project, you will become a specialist in your selected area. You will be encouraged to produce research results of your own. This will prepare you to undertake a PhD in Computer Science should you wish to continue studying within the subject.

Learning outcomes
-A knowledge of several difference topics in Computer Science at an advanced level.
-An understanding of a body of research literature in Computer Science in your chosen topic, and the underlying principles and techniques of research in this area.
-An ability to engage in independent study at an advanced level, and develop skills in self-motivation and organisation.

Research Project

You will undertake your individual research project over the Summer term and Summer vacation. This will be a culmination of the taught modules you have taken during the course, which will allow you to focus on a specialist area of interest.

You will be allocated a personal supervisor, who will be an expert in your chosen area of research. You will be hosted by the research group of your supervisor, and you will benefit from the knowledge and resources of the whole group. Being attached to a research group also allows you to take part in their informal research seminars, and receive feedback and help from other members of the group.

You can choose from projects suggested by members of our academic staff. You also have the option of formulating your own project proposal, with the assistance from your personal supervisor.

All project proposals are rigorously vetted and must meet a number of requirements before these are made available to the students. The department uses an automated project allocation system for assigning projects to students that takes into account supervisor and student preferences.

The project aims to give you an introduction to independent research, as well as giving you the context of a research group working on topics that will be allied to your own. You will develop the skills and understanding in the methods and techniques of research in Computer Science.

As part of the assessment of the project, as well as your dissertation, you will give a talk about your work and submit a concise paper which we will encourage you to publish.

Information for Students

The MSc in Advanced Computer Science exposes you to several topics in Computer Science that are under active research at York. The material taught is preparatory to helping to continue that research, and perhaps continuing to a PhD. What we require from you are enthusiasm, hard work and enough background knowledge to take your chosen modules.

The modules on the MSc in Advanced Computer Science are mostly shared with our Stage 4 (Masters level) undergraduates. Your technical background will be different, and we acknowledge this.

During August we will send entrants a document describing the background knowledge needed for each module and, in many cases, references to where this knowledge is available (for example, widely available text books and web pages).

More generally, many of the modules expect a high level of mathematical sophistication. While the kind of mathematics used varies from module to module, you will find it useful to revise discrete mathematics (predicate and propositional calculi, set theory, relational and functional calculi, and some knowledge of formal logic), statistics and formal language theory. You should also be able to follow and produce proofs.

Careers

Here at York, we're really proud of the fact that more than 97% of our postgraduate students go on to employment or further study within six months of graduating from York. We think the reason for this is that our courses prepare our students for life in the workplace through our collaboration with industry to ensure that what we are teaching is useful for employers.

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Studying Mathematics at postgraduate level gives you a chance to begin your own research, develop your own creativity and be part of a long tradition of people investigating analytic, geometric and algebraic ideas. Read more
Studying Mathematics at postgraduate level gives you a chance to begin your own research, develop your own creativity and be part of a long tradition of people investigating analytic, geometric and algebraic ideas.

If your mathematical background is insufficient for direct entry to the MSc in Mathematics and its Applications, you may apply for this course. The first year of this Master's programme gives you a strong background in mathematics, equivalent to the Graduate Diploma in Mathematics, with second year studies following the MSc in Mathematics and its Applications.

Visit the website https://www.kent.ac.uk/courses/postgraduate/148/international-masters-in-mathematics-and-its-applications

About the School of Mathematics, Statistics and Actuarial Science (SMSAS)

The School has a strong reputation for world-class research and a well-established system of support and training, with a high level of contact between staff and research students. Postgraduate students develop analytical, communication and research skills. Developing computational skills and applying them to mathematical problems forms a significant part of the postgraduate training in the School.

The Mathematics Group at Kent ranked highly in the most recent Research Assessment Exercise. With 100% of the Applied Mathematics Group submitted, all research outputs were judged to be of international quality and 12.5% was rated 4*. For the Pure Mathematics Group, a large proportion of the outputs demonstrated international excellence.

The Mathematics Group also has an excellent track record of winning research grants from the Engineering and Physical Sciences Research Council (EPSRC), the Royal Society, the EU, the London Mathematical Society and the Leverhulme Trust.

Course structure

At least one modern application of mathematics is studied in-depth by each student. Mathematical computing and open-ended project work forms an integral part of the learning experience. You strengthen your grounding in the subject and gain a sound grasp of the wider relevance and application of mathematics.

There are opportunities for outreach and engagement with the public on mathematics.

Modules

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

MA552 - Analysis (15 credits)
MA553 - Linear Algebra (15 credits)
MA588 - Mathematical Techniques and Differential Equations (15 credits)
MA591 - Nonlinear Systems and Mathematical Biology (15 credits)
MA593 - Topics in Modern Applied Mathematics (30 credits)
MA549 - Discrete Mathematics (15 credits)
MA572 - Complex Analysis (15 credits)
MA563 - Calculus of Variations (15 credits)
MA587 - Numerical Solution of Differential Equations (15 credits)
MA577 - Elements of Abstract Analysis (15 credits)
MA576 - Groups and Representations (15 credits)
MA574 - Polynomials in Several Variables (15 credits)
MA961 - Mathematical Inquiry and Communication (30 credits)
MA962 - Geometric Integration (15 credits)
MA964 - Applied Algebraic Topology (15 credits)
MA965 - Symmetries, Groups and Invariants (15 credits)
MA968 - Mathematics and Music (15 credits)
MA969 - Applied Differential Geometry (15 credits)
MA970 - Nonlinear Analysis and Optimisation (15 credits)
MA971 - Introduction to Functional Analysis (15 credits)
MA972 - Algebraic Curves in Nature (15 credits)
MA973 - Basic Differential Algebra (15 credits)
CB600 - Games and Networks (15 credits)
MA562 - Nonlinear Waves and Solitons (15 credits)
MA960 - Dissertation (60 credits)

Assessment

Closed book examinations, take-home problem assignments and computer lab assignments (depending on the module).

Programme aims

This programme aims to:

- provide a Master’s level mathematical education of excellent quality, informed by research and scholarship

- provide an opportunity to enhance your mathematical creativity, problem-solving skills and advanced computational skills

- provide an opportunity for you to enhance your oral communication, project design and basic research skills

- provide an opportunity for you to experience and engage with a creative, research-active professional mathematical environment

- produce graduates of value to the region and nation by offering you opportunities to learn about mathematics in the context of its application.

Study support

Postgraduate resources
The University’s Templeman Library houses a comprehensive collection of books and research periodicals. Online access to a wide variety of journals is available through services such as ScienceDirect and SpringerLink. The School has licences for major numerical and computer algebra software packages. Postgraduates are provided with computers in shared offices in the School. The School has two dedicated terminal rooms for taught postgraduate students to use for lectures and self-study.

Support
The School has a well-established system of support and training, with a high level of contact between staff and research students. There are two weekly seminar series: The Mathematics Colloquium at Kent attracts international speakers discussing recent advances in their subject; the Friday seminar series features in-house speakers and visitors talking about their latest work. These are supplemented by weekly discussion groups. The School is a member of the EPSRC-funded London Taught Course Centre for PhD students in the mathematical sciences, and students can participate in the courses and workshops offered by the Centre. The School offers conference grants to enable research students to present their work at national and international conferences.

Dynamic publishing culture
Staff publish regularly and widely in journals, conference proceedings and books. Among others, they have recently contributed to: Advances in Mathematics; Algebra and Representation Theory; Journal of Physics A; Journal of Symbolic Computations; Journal of Topology and Analysis. Details of recently published books can be found within the staff research interests section.

Global Skills Award
All students registered for a taught Master's programme are eligible to apply for a place on our Global Skills Award Programme (http://www.kent.ac.uk/graduateschool/skills/programmes/gsa.html). The programme is designed to broaden your understanding of global issues and current affairs as well as to develop personal skills which will enhance your employability.

Careers

A postgraduate degree in Mathematics is a flexible and valuable qualification that gives you a competitive advantage in a wide range of mathematically oriented careers. Our programmes enable you to develop the skills and capabilities that employers are looking for including problem-solving, independent thought, report-writing, project management, leadership skills, teamworking and good communication.

Many of our graduates have gone on to work in international organisations, the financial sector, and business. Others have found postgraduate research places at Kent and other universities.

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

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Why choose this course?. This course provides you with a sound general knowledge of advanced mathematics through study in several pure and applied areas of the subject, including Statistics and Operational Research. Read more

Why choose this course?

This course provides you with a sound general knowledge of advanced mathematics through study in several pure and applied areas of the subject, including Statistics and Operational Research. A wide choice of topics is available for your dissertation, taken under the supervision of a member of the academic staff.

If you wish to enter employment within the field of Mathematics then this course will enhance your career prospects by promoting a professional attitude to Mathematics. Mathematicians are warmly welcomed in industry, business and commerce for their analytical ability and logical approach to problem solving. The course is particularly suitable if you are planning a career in teaching Mathematics or are already a qualified teacher seeking to enhance your promotion prospects.

What happens on the course?

Research Methods and professional Skills

Mathematical Modelling

Introduction to Cybermetrics

Statistics

Advanced Topics in Mathematics

Discrete Mathematics

Why Wolverhampton?

The Mathematics department includes a team of researchers in the field of Introduction to Cybermetrics, led by a professor who has been recognised as a leading international authority on the subject and who achieved a very high rating in the latest Research Assessment Exercise.

We pride ourselves on the academic support and guidance given by our friendly and approachable staff. Students have shown their appreciation for this by the exceptionally high ratings they have given us in the National Student Survey in recent years.

Career Path

Students will have developed advanced technical skills within the field of Mathematics together with an ability to critically analyse and evaluate complex problems. These skills should equip students to enter careers in Mathematics in a variety of roles.

There is a shortage of Mathematics-related skills both nationally and regionally, and in particular there is a recognised severe shortage of qualified Mathematics teachers. Hence the Mathematics qualification that this course offers will make its graduates highly employable.

Excellent career opportunities will also be open in operational research, statistics, information analysis, financial advising, actuarial work and accountancy.

What skills will you gain?

You will be able to demonstrate a full understanding, knowledge and experience of complex and specialised areas of mathematics; Select and apply appropriate techniques to the analysis, design and synthesis of solutions to problems which require mathematics for their resolution.

Within this course, you will apply knowledge of mathematics with particular reference to its applications in other subject areas (e.g. mathematical education, analysis and modelling of business and finance, computing and scientific systems).

You will be able to demonstrate originality in the application of knowledge, together with a practical understanding of how established techniques of research and enquiry are used to create and interpret knowledge in mathematics.

Conduct research into current mathematical literature; review, analyse and evaluate findings in a professional manner.

This course will enable you to deal with complex issues both systematically and creatively, making sound judgements in the absence of complete data, and communicating conclusions clearly to specialist and non-specialist audiences.

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This MSc programme takes two years of full-time study, covering a wide spectrum of fields in Computer Science and Information Technology. Read more
This MSc programme takes two years of full-time study, covering a wide spectrum of fields in Computer Science and Information Technology. It is suitable for students with diverse academic backgrounds, such as computer science, engineering, statistics, mathematics and related disciplines.
The programme has been awarded with the GRIN 2015 Quality Label.
GRIN is an Italian association that aims at promoting research and education in Computer Science.

The programme

The programme unfolds into three semesters of full-time lectures and lab experience. During the last semester, students work on an individual project and dissertation, supervised by a department member. The programme is organized around two curricula, which include both compulsory and elective courses, from which students have to build their study plan for qualification. The two curricula, which include a first semester of common courses on advanced topics in computer science and mathematics, are the following:

Data Management and Analytics (DMA)
This curriculum is designed to train a new generation of professionals specialized on data. Specifically, the study program of this curriculum allows students to acquire skills and key competences such as machine learning and artificial intelligence, advanced databases and information retrieval, statistics, data mining and visualization, cloud, distributed and parallel computing.

Software Dependability and Cyber Security (SDCS)
The curriculum aims at training specialists in software engineering with advanced skills in software correctness verification, in design of secure and privacy aware systems, and their performance evaluation. The study program for this profile allows students to acquire skills in system modelling, in evaluating and verifying software requirements in terms of correctness, scalability and performance, in secure programming and cyber security.

Applying to the programme

To enter the programme applicants need to have an equivalent of a three-year Italian undergraduate degree (Laurea) such as a BSc degree in Computer Science or related subject, with good background on fundamental topics in computer science and engineering, such as programming languages and software engineering, algorithms, computer architecture, operating systems, databases, and computer networks. Further requirements include basic knowledge of calculus, discrete mathematics, and probability and statistics, foundations of computer science.

When and how to apply

The classes start in September. Please note that it is best to apply as early as possible. Applications are made directly to the University of Venice. For full details visit How to apply, or contact the Head of Study ().

Graduate careers

Students graduating from the MSc in Computer Science may use their new computing skills to enhance their employment prospects in work related to their first degree. Graduates interested in foundational, experimental, and applied research, can join our PhD Programme in Computer Science.

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1. Big Challenges being addressed by this programme – motivation. Globally, there is a reported shortage of data analytics talent, particularly of individuals with the required deep technical and analytical skills. Read more

About the Course

1. Big Challenges being addressed by this programme – motivation

• Globally, there is a reported shortage of data analytics talent, particularly of individuals with the required deep technical and analytical skills.
• Accenture, Gartner and McKinsey have all identified Data Analytics as one of the fastest growing employment areas in computing and one most likely to make an impact in the future.
• The Irish Government’s policy is for Ireland to become a leading country in Europe for big data and analytics, which would result in 21,000 potential new employment opportunities in Ireland alone.
• CNN has listed jobs in this area in their Top 10 best new jobs in America.

2. Programme objectives & purpose

This is an advanced programme that provides Computing graduates with advanced knowledge and skills in the emerging growth area of Data Analytics. It includes advanced topics such as Large-Scale Data Analytics, Information Retrieval, Advanced Topics in Machine Learning and Data Mining, Natural Language Processing, Data Visualisation and Web-Mining. It also includes foundational modules in topics such as Statistics, Regression Analysis and Programming for Data Analytics. Students on the programme further deepen their knowledge of Data Analytics by working on a project either in conjunction with a research group or with an industry partner.

Graduates will be excellently qualified to pursue careers in national and multinational industries in a wide range of areas. Our graduates currently work for companies as diverse as IBM, SAP, Cisco, Avaya, Google, Fujitsu and Merck Pharmaceuticals as well as many specialised companies and startups. Opportunities will be found in:
• Multinational companies, in Ireland and elsewhere, that provide services and solutions for analytics and big data or whose business depend on analytics and big data technologies;
• Innovative small to medium-sized companies and leading-edge start-ups who provide analytics solutions, services and products or use data analytics to develop competitive advantage
• Companies looking to extend their research and development units with highly trained data analytic specialists
• PhD-level research in NUI Galway, elsewhere in Ireland, or abroad

3. What’s special about CoEI/NUIG in this area:

• The MSc in Computer Science (Data Analytics) is being delivered by the Discipline of Information Technology in collaboration with the Insight Centre for Data Analytics (http://insight-centre.org) and with input from the School of Mathematics, Statistics and Applied Mathematics in NUI Galway
• The Discipline of Information Technology at NUI Galway has 25-year track record of education, academic research, and industry collaboration in the field of Computer Science
• The Insight centre at NUI Galway is Europe’s largest research centre for Data Analytics

4. Programme Structure – ECTS weights and split over semester; core/elective, etc.:

• 90ECTS programme
• one full year in duration, beginning September and finishing August
• comprises:
- Foundational taught modules (20 ECTS)
- Advanced taught modules (40 ECTS)
- Research/Industry Project (30 ECTS).

5. Programme Content – module names

Sample Foundational Modules:

• Tools and Techniques for Large Scale Data Analytics
• Programming for Data Analytics
• Machine Learning and Data Mining
• Modern Information Management
• Probability and Statistics
• Discrete Mathematics
• Applied Regression Models
• Digital Signal Processing

Sample Advanced Modules:

• Advanced Topics in Machine Learning and Information Retrieval
• Web Mining and Analytics
• Systems Modelling and Simulation
• Natural Language Processing
• Data Visualisation
• Linked Data Analytics
• Case Studies in Data Analytics
• Embedded Signal Analysis and Processing

6. Testimonials

Ms. Gofran Shukair, MSc, Research Engineer at ZenDesk, Ireland

After graduating with an MSc at NUI Galway, Gofran worked with Fujitsu’s Irish Research Lab as a research engineer before moving to a software engineering position at Zendesk, Ireland.

“The mix of technical and soft skills I gained through my Masters studies at NUI Galway is invaluable. I had the chance to work with great people and to apply my work on real world problems. With the data management and analysis skills I gained, I am currently pursuing my research in an international research project with one of the leading IT companies. I will be always thankful for studying at NUI Galway, a great historic place based in a culturally-rich vibrant city with an international mix of young and ambitious students that made me eager to learn and contribute back the moment I graduated.”

For further details

visit http://www.nuigalway.ie/courses/taught-postgraduate-courses/msc-in-computer-science-data-analytics.html

How to Apply:

Applications are made online via the Postgraduate Applications Centre (PAC) https://www.pac.ie
Please use the following PAC application code for your programme:

M.Sc. Computer Science – Data Analytics - PAC code GYE06

Scholarships :

Please visit our website for more information on scholarships: http://www.nuigalway.ie/engineering-informatics/internationalpostgraduatestudents/feesandscholarships/

Visit the M.Sc. Computer Science – Data Analytics page on the National University of Ireland, Galway web site for more details!

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