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The M.S. in Applied and Computational Mathematics program is designed to prepare students to join the workforce as a consulting mathematician or to pursue doctoral study in computational and industrial mathematics or other computationally-intensive field of study. Read more
The M.S. in Applied and Computational Mathematics program is designed to prepare students to join the workforce as a consulting mathematician or to pursue doctoral study in computational and industrial mathematics or other computationally-intensive field of study. 

Distinctive features include:

• Project-oriented approach in all courses - real-world industrial problems motivate coursework
• Team problem-solving practica emulate an industrial microcosm in which undergrads, grads, faculty, and industrial partners work together to study real-world problems
• Dual emphasis is placed on computational mathematics in the study of all real-world projects in each course of the curriculum

Students who complete the proposed program will:

• Acquire advanced knowledge of a wide variety of topics that span the realm of applied mathematics, including differential equations, discrete mathematics, probabilistic modelling, optimisation and statistical analysis. 
• Become adept at employing all steps of the mathematical modelling process in the analysis of real-world phenomena.
• Acquire expertise in using various forms of technology and in using, modifying, and creating numerical algorithms used in the analysis of real-world phenomena,
• Develop the valuable intuition of using the right tool for the right job.

Curriculum

Required modules:

MAT 500 Fundamentals of Applied Mathematics
MAT 548 Industrial Mathematics - Continuous Models
MAT 549 Industrial Mathematics - Discrete Models
MAT 552 Operations Research
MAT 553 Stochastic Modelling
MAT 554 Scientific Computing
MAT 555 Industrial Practicum - Continuous Models
STA 505 Mathematical Statistics I
MAT 556 Industrial Practicum - Discrete Models
STA 511 Intro Stat Computing & Data Management

Electives:

One three-credit elective must be chosen from one of the following

MAT 514 Theory Of Numbers
MAT 515 Algebra I
MAT 516 Algebra II
MAT 532 Geometry I
MAT 533 Geometry II
MAT 535 Topology
MAT 545 Real Analysis I
MAT 546 Real Analysis II
MAT 575 Complex Analysis I

An additional three credit elective must be chosen from any 500-level mathematics or statistics course not completed from the above list.

Collaborators and Local Industry

Representatives from the private sector consisting of mathematicians and scientists from large companies such as Vanguard, and PrimePay; employees of up-and-coming software companies such as iPipeline; and representatives of small privately-owned consulting firms and hedge fund companies, such as Wagner Associates and TFS Capital were consulted in the creation of this program.  We are continually expanding our network of collaborators within the private sector, with our newest collaborator being Stroud Preserve in West Chester.

Vastly different types of mathematical problems are studied by the members of this group.  Many have agreed to contribute to this M.S. program by way of delivering colloquium talks about their experiences in industry, and by creating and investigating real-world problems in our practicum courses.

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The course provides a detailed exposure to the context, issues and methods used to analyse the increasingly complex problems which are found in the defence environment and to support decision making. Read more

Course Description

The course provides a detailed exposure to the context, issues and methods used to analyse the increasingly complex problems which are found in the defence environment and to support decision making. It exposes the types of analysis and allows practical experience of tools and methods which are used, ranging from judgemental analysis through mathematical techniques to models and simulations. The course includes judgemental elicitation and analysis techniques, mathematical analysis methods (including optimisation), war gaming and combat modelling, logistics modelling and simulation methods. The use and utility of all the methods are explored through practical exercises and studies.

Course overview

The modular form of the course, consisting of a compulsory core and a selection of Standard and Advanced modules, enables you to select the course of study most appropriate to your particular requirements.

Standard modules normally comprise a week of teaching (or equivalent for distance learning) followed by a further week of directed study/coursework (or equivalent for part time and distance learning).

Advanced modules, which will enable you to explore some areas in greater depth, are two week (or equivalent for part time and distance learning) individual mini-projects on an agreed topic in that subject, which includes a written report and oral presentation.

- MSc students must complete a taught phase consisting of eight standard modules, which includes two core modules (Introduction to Operational Research Techniques and Decision Analysis), plus four advanced modules, followed by an individual thesis in a relevant topic. Thesis topics will be related to problems of specific interest to students and sponsors or local industry wherever possible.
- PgDip students are required to undertake the same taught phase as the MSc, but without the individual thesis.
- PgCert students must complete the core module (Introduction to Operational Research Techniques) together with five other modules; up to three of these may be advanced modules.

On successful completion of the course you will:

- Demonstrate a thorough understanding of the methods, techniques and tools for modelling defence problems and systems
- Be able to critically assess a range of approaches and methods to help support defence analysis and decision-making.

10 places are normally available for the full-time cohort.

The course is suitable for both military and civilian personnel, including those from defence industry and government departments

Individual Project

An individual research project on an agreed topic that allows you to demonstrate your technical expertise, independent learning abilities and critical appraisal skills.

Modules

Part-time students will typically not study as a cohort, but will follow an agreed individual programme of study, attending courses as convenient.
Advanced Modules, which typically comprise individual self-study, can be selected to follow on from any standard modules that have been chosen.
Standard Modules, which typically involve traditional classroom instruction and/or VLE-based delivery, can be chosen from the following:

Core -

Decision Analysis
Introduction to Operational Research Techniques

Optional -

Advanced Decision Analysis
Advanced Discrete and Continuous Simulation
Advanced Logistics Modelling
Advanced War Gaming and Combat Modelling
Applied Optimisation
Computational Statistics
Discrete and Continuous Simulation
Further Operational Research Techniques
Intelligent Systems
Intelligent Systems - Research Study
Logistics Modelling
Neural Networks
Optimisation
Statistical Analysis and Trials
War Gaming and Combat Modelling
Weapon System Performance Assessment

Assessment

Continuous assessment, written examinations, oral vivas and (MSc only) thesis.
Proportions of different assessment types will vary according to programme and elective options chosen. For an MSc these might typically comprise 15-24% continuous assessment (written and oral), 36-45% written examinations and 40% thesis/dissertation.

Career opportunities

Equips you for:

- Appointments within the armed forces or government, or in the defence related activities of commercial organisations.
- Further research leading to a PhD.

Further Information

For further information on this course, please visit our course webpage - http://www.cranfield.ac.uk/Courses/Masters/Military-Operational-Research

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The course addresses the design, development, procurement, use and management of models and simulations for applications in experimentation, training, testing, analysis and assessment of military forces, systems and equipment. Read more

Course Description

The course addresses the design, development, procurement, use and management of models and simulations for applications in experimentation, training, testing, analysis and assessment of military forces, systems and equipment.

Overview

On successful completion of the course you will be familiar with the technologies, methodologies, principles and terminology of Modelling and Simulation as used across defence, including the challenges and issues as well as the benefits. Through use of facilities such as the Simulation and Synthetic Environment Laboratory (SSEL), with its wide range of specialist applications, students will gain a broad understanding of modelling and simulation in areas such as training, acquisition, decision-support, analysis and experimentation.

•10 places are normally available for the full-time cohort
•The course is suitable for both military and civilian personnel, including those from defence industry and government departments

Start date: Full-time: annually in September. Part-time: by arrangement

Duration: Full-time MSc - one year, Part-time MSc - up to three years, Full-time PgCert - one year, Part-time PgCert - two years, Full-time PgDip - one year, Part-time PgDip - two years

English Language Requirements

Students whose first language is not English must attain an IELTS score of 6.5.

Course overview

The modular form of the course, consisting of a compulsory core and a selection of standard and advanced modules, enables each student to select the course of study most appropriate to their particular requirements.

Standard modules normally comprise a week of teaching (or equivalent for distance learning) followed by a further week of directed study/coursework (or equivalent for part time and distance learning).

Advanced modules, which enable students to explore some areas in greater depth, are two week (or equivalent for part time and distance learning) individual mini-projects on an agreed topic in that subject, which includes a written report and oral presentation.

- MSc students must complete a taught phase consisting of eight standard modules, which includes two core modules (Foundations of Modelling and Simulation and Networked and Distributed Simulation), plus four advanced modules, followed by an individual thesis in a relevant topic. Thesis topics will be related to problems of specific interest to students and sponsors of local industry wherever possible.

- PgDip students are required to undertake the same taught phase as the MSc, but without the individual thesis.

- PgCert students must complete the core module (Foundations of Modelling and Simulation) together with five other modules; up to three of these may be advanced modules.

Modules

Part-time students will typically not study as a cohort, but will follow an agreed individual programme of study, attending courses as convenient.
Advanced Modules, which typically comprise individual self-study, can be selected to follow on from any standard modules that have been chosen.
Standard Modules, which typically involve traditional classroom instruction and/or VLE-based delivery, can be chosen from the following:

Core:
- Foundations of Modelling and Simulation
- Networked and Distributed Simulation

Elective:
- Advanced Computer Graphics
- Advanced Discrete and Continuous Simulation
- Advanced Logistics Modelling
- Advanced Modelling and Simulation
- Advanced War Gaming and Combat Modelling
- Computational Statistics
- Computer Graphics
- Discrete and Continuous Simulation
- High Performance and Parallel Computing
- Intelligent Systems
- Intelligent Systems - Research Study
- Logistics Modelling
- Networked and Distributed Simulation Exercise
- Neural Networks
- Programming and Software Development in C
- Statistical Analysis and Trials
- War Gaming and Combat Modelling
- Weapon System Performance Assessment

Individual Project

An individual research project on an agreed topic that allows you to demonstrate your technical expertise, independent learning abilities and critical appraisal skills.

Assessment

Continuous assessment, written examinations, oral vivas and (MSc only) thesis.

Proportions of different assessment types will vary according to programme and modules taken. For an MSc these might typically comprise 15-24% continuous assessment (written and oral), 36-45% written examinations and 40% thesis/dissertation.

Career opportunities

Equips you for simulation-specific appointments within the armed forces or government, or in the defence related activities of commercial organisations.

For further information

On this course, please visit our course webpage http://www.cranfield.ac.uk/Courses/Masters/Defence-Simulation-and-Modelling

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Our Music MLitt enables you to develop a flexible individual research programme in classical, popular, world, contemporary, early, folk and traditional music, applying approaches of interest to you (eg historiographic, theoretical, cultural, critical), under the supervision of specialists who are leaders in their field. Read more
Our Music MLitt enables you to develop a flexible individual research programme in classical, popular, world, contemporary, early, folk and traditional music, applying approaches of interest to you (eg historiographic, theoretical, cultural, critical), under the supervision of specialists who are leaders in their field.

This programme is primarily aimed at students who want to pursue independent musicological research, and who like the idea of first working on shorter research assignments (which can be on related or separate topics), before embarking on an extended final dissertation.

It provides an excellent foundation for continuing on to doctoral study. It is also a valuable qualification in its own right and can add a further dimension to your undergraduate degree, in a 3+1 model.

The MLitt is a modular research programme, which means that it is made up of discrete areas of study:
-Music research training (20 credits)
-Research assignments (80 credits)
-Dissertation (80 credits)

The research assignments are one of the programme’s distinctive features. They allow you to propose and research two or three separate projects (weighted at 40+40, or 20+20+40 credits), which may be connected or on discrete topics, and which lay the ground for your final dissertation. These are completed at the end of April (in year two for part time students) leaving the rest of the programme devoted to your dissertation.

Delivery

The course is delivered on the Newcastle campus (with options – under certain circumstances – for study abroad). All students are required to complete the Music Research Training module during their first two semesters of study and beyond this, study is based on one to one tutorials with supervisors appropriate to your research assignments or dissertation.

The subjects of your Research Assignments and final dissertation require a formal proposal and approval; if these are practicable and within our areas of expertise, these can all be on a topic of your own choosing.

The MLitt is designed primarily with scholarly types of research in mind, but can also accommodate some practical components where appropriate, for example performance in the context of performance practice research.

Facilities

We have outstanding specialist music facilities, including our £4.5m purpose built Music Studios, designed with performance, multimedia and studio-based work in mind.

Additional facilities include:
-Two professional grade recording studios
-A large student common room, including a work area with PCs featuring specialist music software
-A range of recently refurbished rehearsal spaces
-A full range of recently refurbished teaching facilities, including a 100-seat lecture theatre, two 50 seat lecture theatres and three 25-seater seminar rooms
-12 practice rooms with integrated recording facilities
-A dedicated postgraduate workspace
-A project room equipped with 5.1 mixing system

The University Library also has extensive music collections (including a number of important manuscript and microfilm collections), subscribes to many specialist Music journals, has access to a significant body of online resources, and is widely recognised for the supportive service it offers students and staff.

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Master’s Degree in Quantitative Finance and Risk Management draws on the recognized excellence of our engineering school in quantitative finance, and makes great use of the collaborations with the Universities of Paris-Dauphine and Cergy-Pontoise. Read more
Master’s Degree in Quantitative Finance and Risk Management draws on the recognized excellence of our engineering school in quantitative finance, and makes great use of the collaborations with the Universities of Paris-Dauphine and Cergy-Pontoise. The Master is primarily going to appeal to international students, "free movers" or those from our partner universities or for high-potential foreign engineers who are looking for an international career in the domain of finance. This program leads to a Master degree and a Diplôma accredited by the French Ministry of Higher Education and Research.

Objective

This Master’s degree covers the whole chain of quantitative finance, from theoretical aspects to the application in a professional setting. The chain can be described as follows:
o Description of the market and financial products
o Mathematical models of finance
o Mathematical models of risk
o Numerical resolution: computer-aided simulation
o Calibration and asset evaluation

Specific details of the Master:
o The Master came from the Financial Engineering option (IFI) taught at the ESITI for the last 13 years (all students from the option have found work as soon as their compulsory internships finished, and have an average salary 20% higher than the norm in this sector).
o In and of itself, the Master is intrinsically international.
o The theoretical teaching of this Master is very thorough, covering everything needed to know in the associated professions. As a consequence, the students are very adaptable within the work market.
o The Master offers a 3-skilled approach, in Computer Science, Mathematics and Finance.

Practical information
The Master’s degree counts for 120 ECTS (European Credit Transfer System) in total and lasts two years. The training lasts 1316 hours (646 hours in M1 and 670 hours in M2). The semesters are divided as follows:
o M1 courses take place from September until June and count for a total of 60 ECTS
o M2 courses take place from September until mid-April and count for a total of 44 ECTS
o A five-month internship (in France) from mid- April until mid- September for 16 ECTS. Usual indemnities are around 1000 € per month.

Non-French speakers will be asked to participate to a one week intensive French course that precedes the start of the program and allows students to gain the linguistic knowledge necessary for daily interactions.

Organization

M1 modules are taught from September to June (60 ECTS, 646 h):
• Mathematics
• Measure and Integration (2 ECTS, 20 h)
• Functional Analysis (3 ECTS, 30 h)
• Stochastic Processes-Discrete/Continuous Time (5,5 ECTS, 55 h)
• Optimization (2,5 ECTS, 30 h)
• Jump Processes and Application (3 ECTS, 30h)
• Partial Differential Equations (3 ECTS, 30 h)
 Calibration, Simulation and Numerical Analysis
• Monte Carlo Simulations (3 ECTS, 30 h)
• Finite Difference Methods (2,5 ECTS, 25 h)
• Calibration of Financial Models (2 ECTS, 20 h)
• Bloomberg trading room (3ECTS, 30h)
• C++ and Object Oriented Design (2 ECTS, 20 h)
• VBA Programming (3 ECTS, 30 h)
• Interdisciplinary Project (5 ECTS, 5 h)
 Finance and Insurance
• Introduction to Quantitative Finance (3 ECTS, 25 h)
• Risk Management in a mono-period Financial Market & Derivatives (4 ECTS, 40 h)
• Contingent Claims Valuation (3 ECTS, 30 h)
• Portfolio Management and Financial Risks (3 ECTS, 30 h)
• Mathematics Applied to Insurance (3 ECTS, 30 h)
• French as Foreign Language
• French as Foreign Language (4,5 ECTS, 96 h)

M1 modules are taught from September to June (60 ECTS, 646 h):
• Mathematics
• Measure and Integration (2 ECTS, 20 h)
• Functional Analysis (3 ECTS, 30 h)
• Stochastic Processes-Discrete/Continuous Time (5,5 ECTS, 55 h)
• Optimization (2,5 ECTS, 30 h)
• Jump Processes and Application (3 ECTS, 30h)
• Partial Differential Equations (3 ECTS, 30 h)
• Calibration, Simulation and Numerical Analysis
• Monte Carlo Simulations (3 ECTS, 30 h)
• Finite Difference Methods (2,5 ECTS, 25 h)
• Calibration of Financial Models (2 ECTS, 20 h)
• Bloomberg trading room (3ECTS, 30h)
• C++ and Object Oriented Design (2 ECTS, 20 h)
• VBA Programming (3 ECTS, 30 h)
• Interdisciplinary Project (5 ECTS, 5 h)
• Finance and Insurance
• Introduction to Quantitative Finance (3 ECTS, 25 h)
• Risk Management in a mono-period Financial Market & Derivatives (4 ECTS, 40 h)
• Contingent Claims Valuation (3 ECTS, 30 h)
• Portfolio Management and Financial Risks (3 ECTS, 30 h)
• Mathematics Applied to Insurance (3 ECTS, 30 h)
• French as Foreign Language
• French as Foreign Language (4,5 ECTS, 96 h)

M2 modules take place from September to Mid-April (60 ECTS, 670h)
• Mathematics
• Mathematical Statistics (2 ECTS, 21 h)
• Mathematical Tools in Finance (4,5 ECTS, 54h)
• Calibration, Simulation and Numerical Analysis
• Advanced Numerical Methods for PDEs in Finance(2,5 ECTS, 30 h)
• Advanced Spreadsheet Programming (2 ECTS, 24h)
• Simulations (2 ECTS, 24 h)
• Calibration (3 ECTS, 30 h)
• Theoretical and Practical Finance
• Theory of Contingent Claims (4,5 ECTS, 54 h)
• Interest Rate, Exchange and Inflation Markets (2,5 ECTS, 30 h)
• Portfolio Managment (2,5 ECTS, 30 h)
• Imperfect Markets (2 ECTS, 20 h)
• Dynamic Hedging and Risk Measures (2 ECTS, 21 h)
• Business Evaluation (2,5 ECTS, 35 h)
• Jump Processes and Applications (2 ECTS, 21 h)
• Careers and financial products (2 ECTS, 30 h)
• Practical Fixed Income Management (2 ECTS, 24 h)
• French as Foreign Language
• French as Foreign Language (4 ECTS, 72 h)
• Master's Thesis (9 ECTS, 150 h)
• Internship (22 weeks from mid-April to)

Teaching

Fourteen external teachers (lecturers from universities, teacher-researchers, professors etc.), supported by a piloting committee, will bring together the training given in Cergy.

All the classes will be taught in English, with the exception of:
• The class of FLE (French as a foreign language), where the objective is to teach the students how to understand and express themselves in French.
• Cultural Openness, where the objective is to enrich the students’ knowledge of French culture.
The EISTI offers an e-learning site to all its students, which complements everything the students will learn through their presence and participation in class:
• class documents, practical work and tutorials online
• questions and discussions between teachers and students, and among students
• a possibility of handing work in online

All Master’s students are equipped with a laptop for the duration of the program that remains the property of the EISTI.

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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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Computer Science Departmental degree requirements for the master’s degree, which are in addition to those established by the College of Engineering and the Graduate School (http://graduate.ua.edu/), are as follows for Plan I and Plan II students. Read more
Computer Science Departmental degree requirements for the master’s degree, which are in addition to those established by the College of Engineering and the Graduate School (http://graduate.ua.edu/), are as follows for Plan I and Plan II students.

- Master of Science–Thesis Option (http://cs.ua.edu/graduate/ms-program/#thesis)
- Master of Science–Non-Thesis Option (http://cs.ua.edu/graduate/ms-program/#nonthesis)
- Timetable for the Submission of Graduate School Forms for an MS Degree (http://cs.ua.edu/graduate/ms-program/#timetable)

Visit the website http://cs.ua.edu/graduate/ms-program/

MASTER OF SCIENCE–THESIS OPTION (PLAN I):

30 CREDIT HOURS
Each candidate must earn a minimum of 24 semester hours of credit for coursework, plus a 6-hour thesis under the direction of a faculty member. Unlike the general College of Engineering requirements, graduate credit may not be obtained for courses at the 400-level.

Degree Requirements Effective Fall 2011

Credit Hours
The student must successfully complete 30 total credit hours, as follows:

- 24 hours of CS graduate-level course work

- 6 hours of CS 599 Master’s Thesis Research: Thesis Research.

- Completion of at least one 500-level or 600-level course in each of the four core areas (applications, software, systems and theory). These courses must be taken within the department and selected from the following:
Applications: CS 528, CS 535, CS 557, CS 560, CS 609, CS 615
Software: CS 503, CS 507, CS 515, CS 516, CS 534, CS 600, CS 603, CS 607, CS 614, CS 630
Systems: CS 526, CS 538, CS 567, CS 606, CS 613, CS 618
Theory: CS 500, CS 570, CS 575, CS 601, CS 602, CS 612

- No more than 12 hours from CS 511, CS 512, CS 591, CS 592, CS 691, CS 692 and non-CS courses may be counted towards the coursework requirements for the master’s degree. Courses taken outside of CS are subject to the approval of the student’s advisor.

- Additional Requirements -

- The student will select a thesis advisor and a thesis committee. The committee must contain at least four members, including the thesis advisor. At least two members are faculty of the Computer Science department, and at least one member must be from outside the Department of Computer Science.

- The student will develop a written research proposal. This should contain an introduction to the research area, a review of relevant literature in the area, a description of problems to be investigated, an identification of basic goals and objectives of the research, a methodology and timetable for approaching the research, and an extensive bibliography.

- The student will deliver an oral presentation of the research proposal, which is followed by a question-and-answer session that is open to all faculty members and which covers topics related directly or indirectly to the research area. The student’s committee will determine whether the proposal is acceptable based upon both the written and oral presentations.

- The student will develop a written thesis that demonstrates that the student has performed original research that makes a definite contribution to current knowledge. Its format and content must be acceptable to both the student’s committee and the Graduate School.

- The student will defend the written thesis. The defense includes an oral presentation of the thesis research, followed by a question-and-answer session. The student’s committee will determine whether the defense is acceptable.

- The student will complete an oral comprehensive exam. This exam is scheduled with the Department Head prior to the semester in which the student intends to graduate.

- Other requirements may be specified by the Graduate School (http://graduate.ua.edu/) and by the College of Engineering.

Degree Requirements Prior to Fall 2011

Credit hours

The student must successfully complete 30 total credit hours, as follows:

- 6 hours of CS 599 Master’s Thesis Research

- 24 hours of CS graduate-level course work with a grade of A or B, including the following courses completed at The University of Alabama:
At least 3 hours of theory courses (CS 500 Discrete math, CS 601 Algorithms, CS 602 Formal languages, CS 612 Data structures)

At least 3 hours of software courses (CS 600 Software engineering, CS 603 Programming languages, CS 607 Human-computer interaction, CS 614 Compilers, CS630 Empirical Software Engineering)

At least 3 hours of systems courses (CS 567 Computer architecture, CS 606 Operating systems, CS 613 Networks, CS 618 Wireless networks)

At least 3 hours of applications courses (CS 535 Graphics, CS 560 or 591 Robotics, CS 591 Security, CS 609 Databases)

- Additional Requirements -

- The student will select a thesis advisor and a thesis committee. The committee must contain at least four members, including the thesis advisor. At least two members are faculty of the Computer Science department, and at least one member must be from outside the Department of Computer Science.

- The student will develop a written research proposal. This should contain an introduction to the research area, a review of relevant literature in the area, a description of problems to be investigated, an identification of basic goals and objectives of the research, a methodology and timetable for approaching the research, and an extensive bibliography.

- The student will deliver an oral presentation of the research proposal, which is followed by a question-and-answer session that is open to all faculty members and which covers topics related directly or indirectly to the research area. The student’s committee will determine whether the proposal is acceptable based upon both the written and oral presentations.

- The student will develop a written thesis that demonstrates that the student has performed original research that makes a definite contribution to current knowledge. Its format and content must be acceptable to both the student’s committee and the Graduate School.

- The student will defend the written thesis. The defense includes an oral presentation of the thesis research, followed by a question-and-answer session. The student’s committee will determine whether the defense is acceptable.

- The student will complete an oral comprehensive exam. This exam is scheduled with the Department Head prior to the semester in which the student intends to graduate.

- Other requirements may be specified by the Graduate School (http://graduate.ua.edu/) and by the College of Engineering.

MASTER OF SCIENCE–NON-THESIS OPTION (PLAN II):

30 CREDIT HOURS
Each candidate must earn a minimum of 30 semester hours of credit for coursework, which may include a 3-hour non-thesis project under the direction of a faculty member. Unlike the general College of Engineering requirements, graduate credit may not be obtained for courses at the 400-level.

Degree Requirements Effective Fall 2011

The student must successfully complete 30 total credit hours, as follows:

- Completion of at least one 500-level or 600-level course in each of the four core areas (applications, software, systems and theory).
Applications: CS 528, CS 535, CS 557, CS 560, CS 609, CS 615
Software: CS 503, CS 507, CS 515, CS 516, CS 534, CS 600, CS 603, CS 607, CS 614, CS 630
Systems: CS 526, CS 538, CS 567, CS 606, CS 613, CS 618
Theory: CS 500, CS 570, CS 575, CS 601, CS 602, CS 612

- No more than 12 hours from CS 511, CS 512, CS 591, CS 592, CS 691, CS 692 and non-CS courses may be counted towards the coursework requirements for the master’s degree. Courses taken outside of CS are subject to the approval of the student’s advisor.

- The student may elect to replace 3 hours of course work with 3 hours of CS 598 Research Not Related to Thesis: Non-thesis Project. This course should be proposed in writing in advance, approved by the instructor, and a copy placed in the student’s file. The proposal should specify both the course content and the specific deliverables that will be evaluated to determine the course grade.

- Additional Requirements -

- The student will complete an oral comprehensive exam. This exam is scheduled with the Department Head prior to the semester in which the student intends to graduate.

- Other requirements may be specified by the Graduate School and by the College of Engineering.

Degree Requirements Prior to Fall 2011

Credit hours

The student must successfully complete 30 total credit hours of CS graduate-level course work with a grade of A or B, as follows:

- The following courses will be completed at The University of Alabama:
At least 3 hours of theory courses (CS 500 Discrete math, CS 601 Algorithms, CS 602 Formal languages, CS 612 Data structures)

At least 3 hours of software courses (CS 600 Software engineering, CS 603 Programming languages, CS 607 Human-computer interaction, CS 614 Compilers, CS630 Empirical Software Engineering)

At least 3 hours of systems courses (CS 567 Computer architecture, CS 606 Operating systems, CS 613 Networks, CS 618 Wireless networks)

At least 3 hours of applications courses (CS 535 Graphics, CS 560 or 591 Robotics, CS 591 Security, CS 609 Databases)

- The student may elect to replace 3 hours of course work with 3 hours of CS 598 Research Not Related to Thesis: Non-thesis Project. This course should be proposed in writing in advance, approved by the instructor, and a copy placed in the student’s file. The proposal should specify both the course content and the specific deliverables that will be evaluated to determine the course grade.

- Additional Requirements -

- The student will complete an oral comprehensive exam. This exam is scheduled with the Department Head prior to the semester in which the student intends to graduate.

- Other requirements may be specified by the Graduate School and by the College of Engineering.

TIMETABLE FOR THE SUBMISSION OF GRADUATE SCHOOL FORMS FOR AN MS DEGREE
This document identifies a timetable for the submission of all Graduate School paperwork associated with the completion of an M.S. degree

- For students in Plan I students only (thesis option) after a successful thesis proposal defense, you should submit the Appointment/Change of a Masters Thesis Committee form

- The semester before, or no later than the first week in the semester in which you plan to graduate, you should “Apply for Graduation” online in myBama.

- In the semester in which you apply for graduation, the Graduate Program Director will contact you about the Comprehensive Exam.

Find out how to apply here - http://graduate.ua.edu/prospects/application/

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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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This masters is run jointly with Heriot-Watt University. It provides you with expertise in financial mathematics, including stochastic calculus, and a range of practical techniques for analysing financial markets. Read more

This masters is run jointly with Heriot-Watt University. It provides you with expertise in financial mathematics, including stochastic calculus, and a range of practical techniques for analysing financial markets. You will also learn quantitative skills for developing and managing risk that are in high demand since the recent financial crisis.

Adding depth to your learning, our work placement programme puts you at the heart of organisations such as Aberdeen Asset Management, Moody’s Analytics and Lloyds Banking Group.

Programme structure

This programme involves two taught semesters of compulsory and option courses, followed by a dissertation project.

Compulsory courses:

  • Credit Risk Modelling
  • Derivatives Markets
  • Derivative Pricing and Financial Modelling
  • Discrete-Time Finance
  • Financial Markets
  • Special Topics 1
  • Special Topics 2
  • Stochastic Analysis in Finance

Option courses:

  • Deterministic Optimization Methods in Finance
  • Financial Econometrics
  • Portfolio Theory
  • Numerical Techniques of Partial Differential Equations
  • Optimization Methods in Finance
  • Simulation
  • Statistical Methods
  • Statistical Inference
  • Time Series Analysis
  • Stochastic Control and Dynamic Asset Allocation

Career opportunities

Graduates typically work in major financial institutions or continue their studies by joining PhD programmes.



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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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Our MSc Economics programmes are intended to deepen your knowledge and understanding of economics as an academic discipline. Read more
Our MSc Economics programmes are intended to deepen your knowledge and understanding of economics as an academic discipline. Each programme draws upon the internationally-rated research undertaken within the department and the experience of our academics in developing economic policy at organisations such as such as the Bank of England, the Organisation for Economic Cooperation and Development (OECD), the International Monetary Fund (IMF), and the United Nations.

A central objective of all of the programmes is to provide you with insight into the latest thinking in economics. You will attend a series of research seminars, during which you can discuss and present current research papers. You can also participate in the departmental seminars, which attract external academics and provide you with the opportunity to gain insight into current research in economics and econometrics.

Our postgraduate economics degrees form part of the ESRC South West Doctoral Training Centre – a hub of world-class social sciences research. For UK and EU students, this means you can apply to the ESRC for funding assistance with both tuition fees and living expenses if you are intending to progress to a PhD. More information about SWDTC at http://www.exeter.ac.uk/doctoralcollege/fundedcentres/swdtc/.

The MSc Economics is the most general of our programmes and offers the greatest flexibility. It gives you the opportunity to acquire professional training in mainstream economics, including analytical techniques as well as subject-specific knowledge. The programme aims to provide you with a rigorous training in the techniques of economic and econometric analysis, as an aide to understanding contemporary economic issues.

We also provide the opportunity for you to specialise in two discrete areas of Economics and for these specialisms to be reflected in your degree title. Our MSc Economics and Econometrics and MSc Economics and Experimental Economics give you the opportunity to focus on two areas in which the Department of Economics has considerable expertise and experience.

Study abroad and gain a second Masters qualification

The double degree option enables you to gain a second Masters qualification by studying for a year with one of our prestigious partner universities. Specific to this programme is a Double Degree opportunity with Fudan University School of Economics. For more information on this and other postgraduate study abroad opportunities, visit the Business School’s Study Abroad webpages at http://business-school.exeter.ac.uk/programmes/postgraduate/studyabroad/.

Programme structure

During the programme you will study modules (including the dissertation) totalling 180 credits. Please note that programme structures may be subject to change. Descriptions of the individual modules are given in full on the Business School postgraduate module list http://business-school.exeter.ac.uk/programmes/postgraduate/modules/ .

Compulsory modules

Recent examples of compulsory modules are as follows; Macroeconomics ; Microeconomics Quantitative Research Techniques; Optimization Techniques for Economists; Game Theory and Industrial Organisation and Research Design and Dissertation.

Optional modules

Some recent examples are as follows; Topics in Financial Economics; Banking and Financial Services; Domestic and International Portfolio Management; Economics of Corporate Finance; Financial Econometrics; International Trade and Regional Integration; Economics of Banking; Advanced Econometrics and Experimental and Behavioural Economics

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This programme focuses on the mathematical and statistical methods relevant to financial markets, and the skills and knowledge needed to apply them in practice. Read more
This programme focuses on the mathematical and statistical methods relevant to financial markets, and the skills and knowledge needed to apply them in practice.

You will gain knowledge of advanced finance concepts while developing quantitative, mathematical and research skills. The programme covers key topics including financial derivative pricing, discrete and continuous time models, risk management and portfolio optimisation, as well as statistical methods for finance.

This Masters is ideal if you have previously studied accounting and finance, economics, mathematics, physics or computing, and are interested in gaining an understanding of how your skills can be applied to financial markets.

It is also an excellent qualification if you are seeking to pursue further postgraduate study, and is recognised by the Engineering and Physical Sciences Research Council (EPSRC).

Your Career

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

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 UKGovernment Actuary’s Department.

We help you to achieve your career ambitions by providing professional development support as part of the Masters programme.

Apply now

The deadline for International applications is 31 March 2017.
The deadline for UK/EU applications is 31 August 2017.
For further guidance on how to apply, visit: http://business.leeds.ac.uk/masters/how-to-apply/

Online events

You can logon from anywhere to join one of these one hour events, which will include:

- Introduction to Leeds University Business School and Masters study
- Advice from one of our Professional Development Tutors, with examples of the career skills you can build and the major companies we work with
- Guidance on how to apply for postgraduate study from our admissions team
- Opportunity to ask your questions

The dates for our next online events are below:

- TBC

Open events

Our Masters Open Days are an opportunity to visit in person, learn more about our Masters degrees and meet our staff. Activities include:

- Presentations, talks and Q&A with academic directors
- Business School tour
- Speak to admissions, academic teaching teams and current Masters students

Our next Masters Open Day:

- TBC

Please visit our website for further information and to book your place: http://business.leeds.ac.uk/masters/meet-us-at-an-event/

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

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

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

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

Why choose this course?

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

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

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

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

Department research and industry highlights

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

Course content and structure

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Assessment

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

Employability & career opportunities

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

How to apply

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

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This course provides you with a specialist combination of theoretical academic study and robust practical application and skills development in English language teaching. Read more
This course provides you with a specialist combination of theoretical academic study and robust practical application and skills development in English language teaching. It provides advanced training for TESOL professionals, and examines the latest developments in TESOL methodology and related issues. You will develop the practical and professional skills involved in TESOL, along with the ability to analyse and apply theoretical perspectives to practical situations.

The course enables you to develop your skills in argument, synthesis and critical expression of TESOL issues, and apply them in different teaching contexts. You will also enhance your advanced skills of research, presentation and analysis in TESOL contexts. Nurturing ongoing professional development and skills in pursuing further independent research is an important aspect of the course, enabling you to make a full contribution to professional development in your specialist area.

Course content

The course consists of three core modules and a range of option modules. The Language and Learning: Description and Analysis core module introduces in-depth exploration of the core concepts in the description and analysis of language and language learning, with specific reference to English language teaching and second language acquisition. The Current Developments in Language Teaching core module examines a wide range of current practice and developments, including communicative competence in language learning and teaching, language teaching methodology, and discrete and integrated skills. The Dissertation is the third core module.

Modules

The following modules are indicative of what you will study on this course.

Core modules
-CURRENT DEVELOPMENTS IN LANGUAGE TEACHING
-DISSERTATION
-LANGUAGE AND LEARNING: DESCRIPTION AND ANALYSIS

Option modules
-ANALYSING SPOKEN AND WRITTEN DISCOURSE
-EDUCATIONAL MANAGEMENT IN TESOL
-INTERCULTURAL COMMUNICATIVE COMPETENCE
-LANGUAGES FOR SPECIFIC PURPOSES
-MATERIALS DEVELOPMENT
-SOCIOLINGUISTICS
-TESTING AND ASSESSMENT
-USING LITERATURE IN ENGLISH LANGUAGE TEACHING

Associated careers

The course enables you to make substantial progress as advanced English Language Teaching practitioners and managers in a variety of national, regional and cultural educational systems. You will have the training and preparation to make significant contributions as instructors, managers and researchers.

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This one year, residential, taught M.Sc. Read more
This one year, residential, taught M.Sc. provides graduate students, scientists and clinicians with highly advanced theoretical and practical understanding of human reproductive biology, embryology, infertility and assisted reproductive technology (ART) along with intensive ‘hands-on’ practical training in essential laboratory skills and the sophisticated gamete micromanipulation techniques associated with ART. The MSc course is based alongside Oxford Fertility in purpose-built premises, the Institute of Reproductive Sciences, with dedicated state-of-the-art teaching and research facilities.

Course Aims

Our broad intention is to inspire, motivate and train a network of future leaders in clinical embryology throughout the world. Additionally, our students benefit from intensive training in a range of laboratory skills highly suitable for a research career in reproductive science.

Course Structure

The course runs over a period of one year, from October to September, incorporating the three University terms: Michaelmas, Hilary and Trinity. Fundamental reproductive science and laboratory methods/practical skills are taught in the first term (Michaelmas) over five discrete modules. Applied and clinical aspects are delivered in the second term (Hilary) over a further set of five modules. Each module is delivered over a period of one to three weeks and together, the ten modules comprise the ‘core content’ of the course. The third term (Trinity) is extended to allow sufficient time for a high quality research project.

Application Deadline

The deadline for applications for the MSc in Clinical Embryology starting in October 2017 is 12 noon (midday) BST on Friday 21st July 2017. Please see our Graduate Admissions page for further details: http://www.ox.ac.uk/admissions/graduate/courses/msc-clinical-embryology

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