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Masters Degrees (Computational Math)

We have 10 Masters Degrees (Computational Math)

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The master of science in computational finance is designed for students interested in computational or quantitative finance careers in banking, finance, and a growing number of additional industries. Read more

Program overview

The master of science in computational finance is designed for students interested in computational or quantitative finance careers in banking, finance, and a growing number of additional industries. Professionals in these fields use their strengths in business, modeling, and data analysis to understand and use complex financial models, often involving differential and stochastic calculus.

The program addresses a vital and growing career field, reaching beyond banking and finance. Typical job titles include risk analyst, research associate, quantitative analyst, quantitative structured credit analyst, credit risk analyst, quantitative investment analyst, quantitative strategist, data analyst, senior data analyst, fixed income quantitative analyst, and financial engineer. Computational finance is an excellent career option for technically-oriented professionals in the fields of business, math, engineering, economics, statistics, and computer science. Programming knowledge is highly preferred.

Plan of study

The curriculum offers an integration of finance, mathematics, and computing. The required mathematics courses have substantial financial content and the experiential computational finance course, which students take during the summer, makes use of skills learned in the mathematics, analytics, and finance courses taken up to that point. The program has a strong multidisciplinary nature and combines the expertise of four of RIT's colleges. The program is a full-time, 17-month curriculum beginning exclusively in the fall. The program ends with a required non-credit comprehensive exam based on the courses completed by the student.

Curriculum

Computational finance, MS degree, typical course sequence:
-Accounting for Decision Makers
-Survey of Finance
-Equity Analysis
-Debt Analysis
-Advanced Derivatives
-Mathematics for Finance I
-Mathematics for Finance II
-Analytics Electives
-Electives
-Computational Finance Experience

Other admission requirements

-Submit official transcripts (in English) from all previously completed undergraduate and graduate course work.
-Submit the results of the Graduate Management Admission Test (GMAT) or Graduate Record Exam (GRE) (GMAT preferred).
-Submit a personal statement (Applicants should explain why their background, please indicate mathematical and programming knowledge, and interests make them suitable for the program).
-Submit a current resume, and complete a graduate application.
-International applicants whose native language is not English must submit scores from the Test of English as a Foreign Language. Minimum scores of 580 (paper-based) or 92 (Internet-based) are required. Scores from the International English Language Testing System (IELTS) will be accepted in place of the TOEFL exam. The minimum acceptable score is 7.0. The TOEFL or IELTS requirement is waived for native speakers of English or for those submitting transcripts from degrees earned at American institutions. For additional information on the IELTS, visit http://www.ielts.org.
-Completed applications for admission should be on file in the Office of Graduate Enrollment Services at least four weeks prior to registration for the next academic semester for students from the United States, and up to 10 weeks prior for international students applying for student visas.
-Accepted students can defer enrollment for up to one year. After one year, a new application must be submitted and will be re-evaluated based on the most current admission standards.

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This interdisciplinary Masters degree provides you with a broad background in some mainstream and modern aspects of mathematics and computer science. Read more

This interdisciplinary Masters degree provides you with a broad background in some mainstream and modern aspects of mathematics and computer science. You’ll be introduced to sophisticated techniques at the forefront of both disciplines.

The programme combines teaching and research from the School of Mathematics and the School of Computing. Based on the Schools’ complementary research strengths the programme follows two main strands:

  • Algorithms and complexity theory
  • Numerical methods and parallel computing

You’ll have the choice to specialise in one of these strands, gaining specialist knowledge and skills that will prepare you for a wide range of careers. You’ll also develop your research skills when you complete your dissertation.

If you do not meet the full academic entry requirements then you may wish to consider the Graduate Diploma in Mathematics. This course is aimed at students who would like to study for a mathematics related MSc course but do not currently meet the entry requirements. Upon completion of the Graduate Diploma, students who meet the required performance level will be eligible for entry onto a number of related MSc courses, in the following academic year.

Course content

It is expected that you will specialise in one of two areas during the course, although this is not essential.

The two strands are:

Algorithms and complexity theory and connections to logic and combinatorics

This concerns the efficiency of algorithms for solving computational problems, and identifies hierarchies of computational difficulty. This subject has applications in many areas, such as distributed computing, algorithmic tools to manage transport infrastructure, health informatics, artificial intelligence, and computational biology.

Numerical methods and parallel computing

Many problems, in mathematics, physics, astrophysics and biology cannot be solved using analytical techniques and require the application of numerical algorithms for progress. The development and optimisation of these algorithms coupled to the recent increase in computing power via the availability of massively parallel machines has led to great advances in many fields of computational mathematics. This subject has applications in many areas, such as combustion, lubrication, atmospheric dispersion, river and harbour flows, and many more.

For information on typical modules, read Mathematics and Computer Science MSc in the course catalogue

Learning and teaching

Teaching is carried out through a mixture of lectures and smaller group activities such as workshops. Most modules are assessed by a mix of coursework and written examinations. There is also the opportunity to complete a summer project which is individually supervised by a member of staff.

Assessment

The taught course is primarily assessed by end-of-semester examinations with a small component of continuous assessment. The semester three project is assessed by a written dissertation and a short oral presentation.

Career opportunities

Each of these areas offers many career options, and the MSc will provide you with both technical and transferrable skills, for example, conducting an extended and independent research project. It will also offer you excellent preparation for doctoral research in these or related subjects. On completion of the degree you can progress onto a wide range of opportunities including:

  • PhD in Mathematics, or in Computer Science
  • Careers in Computing and Industries which require algorithmic tools (transport infrastructure, health informatics, computational biology, artificial intelligence, companies developing the internet (e.g. search engines).
  • Many other careers (e.g. in Finance) where a mathematics background is valued.

In collaboration with both industrial and academic partners, our research has resulted in computational techniques, and software, that has been widely applied. Our industry links are extensive and include companies such as Google, Yahoo, Akamai, Microsoft, and Tracsis, as well as the NHS.

Careers support

We encourage you to prepare for your career from day one. That’s one of the reasons Leeds graduates are so sought after by employers.

The Careers Centre and staff in your faculty provide 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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Technologies based on the intelligent use of data are leading to great changes in our everyday life. Data Science and Engineering refers to the know-how and competence required to effectively manage and analyse the massive amount of data available in a wide range of domains. Read more
Technologies based on the intelligent use of data are leading to great changes in our everyday life. Data Science and Engineering refers to the know-how and competence required to effectively manage and analyse the massive amount of data available in a wide range of domains.

We offer a two-year Master of Science in Computer Science centered on this emerging field. The backbone of the program is constituted by three core units on advanced data management, machine learning, and high performance computing. Leveraging on the expertise of our faculty, the rest of the program is organised in four tracks, Business Intelligence, Health & Life Sciences, Pervasive Computing, and Visual Computing, each providing a solid grounding in data science and engineering as well as a firm grasp of the domain of interest.

By blending standard classes with recitations and lab sessions our program ensures that each student masters the theoretical foundations and acquires hands-on experience in each subject. In most units credit is obtained by working on a final project. Additional credit is also gained through short-term internship in the industry or in a research lab. The master thesis is worth 25% of the total credit.

TRACKS

• Business Intelligence. This track builds on first hand knowledge of business management and fundamentals of data warehousing, and focuses on data mining, graph analytics, information visualisation, and issues related to data protection and privacy.
• Health & Life Sciences. Starting from core knowledge of signal and image processing, bioinformatics and computational biology, this track covers methods for biomedical image reconstruction, computational neuroengineering, well-being technologies and data protection and privacy.
• Pervasive Computing. Security and ubiquitous computing set the scene for this track which deals with data semantics, large scale software engineering, graph analytics and data protection and privacy.
• Visual Computing. This track lays the basics of signal & image processing and of computer graphics & augmented reality, and covers human computer interaction, computational vision, data visualisation, and computer games.

PROSPECTIVE CAREER

Senior expert in Data Science and Engineering. You will be at the forefront of the high-tech job market since all big companies are investing on data driven approaches for decision making and planning. The Business Intelligence area is highly regarded by consulting companies and large enterprises, while the Health and Life Sciences track is mainly oriented toward biomedical industry and research institutes. Both the Pervasive and the Visual Computing tracks are close to the interests of software companies. For all tracks a job in a start-up company or a career on your own are always in order.

Senior computer scientist.. By personalizing your plan of study you can keep open all the highly qualified job options in software companies.

Further graduate studies.. In all cases, you will be fully qualified to pursue your graduate studies toward a PhD in Computer Science.

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This programme trains you in the methods and techniques to apply mathematics to the real world, with a particular emphasis on problem solving and an exposure to different disciplines and industrial problems. Read more
This programme trains you in the methods and techniques to apply mathematics to the real world, with a particular emphasis on problem solving and an exposure to different disciplines and industrial problems.

The programme aims to provide innovative training in interdisciplinary applied mathematics and modern scientific computing. It links mathematics with engineering, biology and other sciences, and gives students direct contact with industry.

It develops an awareness of modern applications of mathematics in an interdisciplinary environment, provides training in mathematical methods, mathematical modelling, scientific computation and other applied techniques, and bridges the gap between theory and applications.

Why study Mathematical Sciences with us?

- Consistently ranked in the top ten of Mathematics league tables
- The most recent assessment of the quality of research being done in academic departments across the UK, (RAE 2008), confirms that our research activity is at the forefront of international excellence
- We have a fully-supported professional placement programme.

Visit the website http://www.bath.ac.uk/science/graduate-school/taught-programmes/msc-modern-application-of-mathematics/

What will I learn?

The MSc Modern Applications of Mathematics specialises in interdisciplinary applications of mathematics, notably in industry and mathematical biology. There is the possibility of a six month placement with industry.

The MSc combines a thorough education in core areas of applied mathematics with interdisciplinary training; there is a wide range of interdisciplinary units to choose from, ranging from astrophysics over cryptography to computational chemistry.

The theory elements will be developed in context, with the students doing an applications based project.

The MSc benefits strongly from close interactions with many industrial companies who come to meet the students and to offer projects. Recent project partners have included:

BAE systems
Airbus
the Met Office
SERCO
Schlumberger
BT
RHM Food Technology
QinetiQ
Hoare-Lea Acoustics

We offer a six month industrial placement as alternative to a three-month project, both leading to a dissertation.

This placement gives the opportunity to work in a company for an extended period of time and to gain in this way first-hand experience in industrial applications of mathematics. Several companies have funded places on offer.

For further information please visit our department pages (http://www.bath.ac.uk/math-sci/).

Career opportunities

Our graduates have gone on to further research in Lausanne, Berlin, Brussels, Frankfurt, and academic posts in Malaysia, Sweden, Germany, Canada, the US and in the UK. Recent employers of Bath graduates include:

British Aerospace
Network Rail
Powergen
Barclays Capital
BNP Paribas
Pfizer
AstraZenaca
MBDA UK Ltd
ATASS

Find out more about the department here - http://www.bath.ac.uk/math-sci/

Find out how to apply here - http://www.bath.ac.uk/science/graduate-school/taught-programmes/how-to-apply/

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