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Masters Degrees (Numerical Analysis)

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The Applied Mathematics group in the School of Mathematics at the University of Manchester has a long-standing international reputation for its research. Read more
The Applied Mathematics group in the School of Mathematics at the University of Manchester has a long-standing international reputation for its research. Expertise in the group encompasses a broad range of topics, including Continuum Mechanics, Analysis & Dynamical Systems, Industrial & Applied Mathematics, Inverse Problems, Mathematical Finance, and Numerical Analysis & Scientific Computing. The group has a strongly interdisciplinary research ethos, which it pursues in areas such as Mathematics in the Life Sciences, Uncertainty Quantification & Data Science, and within the Manchester Centre for Nonlinear Dynamics.

The Applied Mathematics group offers the MSc in Applied Mathematics as an entry point to graduate study. The MSc has two pathways, reflecting the existing strengths within the group in numerical analysis and in industrial mathematics. The MSc consists of five core modules (total 75 credits) covering the main areas of mathematical techniques, modelling and computing skills necessary to become a modern applied mathematician. Students then choose three options, chosen from specific pathways in numerical analysis and industrial modelling (total 45 credits). Finally, a dissertation (60 credits) is undertaken with supervision from a member of staff in the applied mathematics group with the possibility of co-supervision with an industrial sponsor.

Aims

The course aims to develop core skills in applied mathematics and allows students to specialise in industrial modelling or numerical analysis, in preparation for study towards a PhD or a career using mathematics within industry. An important element is the course regarding transferable skills which will link with academics and employers to deliver important skills for a successful transition to a research career or the industrial workplace.

Special features

The course features a transferable skills module, with guest lectures from industrial partners. Some dissertation projects and short internships will also be available with industry.

Teaching and learning

Students take eight taught modules and write a dissertation. The taught modules feature a variety of teaching methods, including lectures, coursework, and computing and modelling projects (both individually and in groups). The modules on Scientific Computing and Transferable Skills particularly involve significant project work. Modules are examined through both coursework and examinations.

Coursework and assessment

Assessment comprises course work, exams in January and May, followed by a dissertation carried out and written up between June and September. The dissertation counts for 60 credits of the 180 credits and is chosen from a range of available projects, including projects suggested by industrial partners.

Course unit details

CORE (75 credits)
1. Mathematical methods
2. Partial Differential Equations
3. Scientific Computing
4. Dynamical Systems
5. Transferrable skills for mathematicians

Industrial modelling pathway
1 Continuum mechanics
2. Stability theory
3. Conservation and transport laws

Numerical analysis pathway
1. Numerical linear algebra
2. Finite Elements
3. Optimization and variational calculus

Career opportunities

The programme will prepare students for a career in research (via entry into a PhD programme) or direct entry into industry. Possible subsequent PhD programmes would be those in mathematics, computer science, or one of the many science and engineering disciplines where applied mathematics is crucial. The programme develops many computational, analytical, and modelling skills, which are valued by a wide range of employers. Specialist skills in scientific computing are valued in the science, engineering, and financial sector.

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Applied Mathematical Sciences offers a clear and relevant gateway into a successful career in business, education or scientific research. Read more
Applied Mathematical Sciences offers a clear and relevant gateway into a successful career in business, education or scientific research. The programme arms students with the essential knowledge required by all professional mathematicians working across many disciplines. You will learn to communicate their ideas effectively to peers and others, as well as the importance of research, planning and self-motivation.

Students will take a total of 8 courses, 4 in each of the 1st and 2nd Semesters followed by a 3-month Project in the summer. A typical distribution for this programme is as follows:

Core courses

:

Modelling and Tools;
Optimization;
Dynamical Systems;
Applied Mathematics (recommended);
Applied Linear Algebra (recommended).

Optional Courses

:

Mathematical Ecology;
Functional Analysis;
Numerical Analysis of ODEs;
Pure Mathematics;
Statistical Methods;
Stochastic Simulation;
Software Engineering Foundations;
Mathematical Biology and Medicine;
Partial Differential Equations;
Numerical Analysis;
Geometry.

Typical project subjects

:

Pattern Formation of Whole Ecosystems;
Climate Change Impact;
Modelling Invasive Tumour Growth;
Simulation of Granular Flow and Growing Sandpiles;
Finite Element Discretisation of ODEs and PDEs;
Domain Decomposition;
Mathematical Modelling of Crime;
The Geometry of Point Particles;
Can we Trust Eigenvalues on a Computer?

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he contribution of mathematical and computational modelling to the understanding of biological systems has rapidly grown in recent years. Read more
he contribution of mathematical and computational modelling to the understanding of biological systems has rapidly grown in recent years. This discipline encompasses a wide range of life science areas, including ecology (e.g. population dynamics), epidemiology (e.g. spread of diseases), medicine (e.g. modelling cancer growth and treatment) and developmental biology.

This programme aims to equip students with the necessary technical skills to develop, analyse and interpret models applied to biological systems. Course work is supported by an extended and supervised project in life science modelling.

Students will take a total of 8 courses, 4 in each of the 1st and 2nd Semesters followed by a 3-month Project in the summer. A typical distribution for this programme is as follows:

Core courses

Modelling and Tools;
Mathematical Ecology;
Dynamical Systems;
Mathematical Biology and Medicine.

Optional Courses

Optimization;
Numerical Analysis of ODEs;
Applied Mathematics;
Statistical Methods;
Stochastic Simulation;
Partial Differential Equations;
Numerical Analysis;
Geometry;
Climate Change: Causes and Impacts;
Biologically Inspired Computation;
Climate Change: Mitigation and Adaptation Measures.

Typical project subjects

Population Cycles of Forest Insects;
Modelling Invasive Tumour Growth;
The replacement of Red Squirrels by Grey Squirrels in the UK;
Wiring of Nervous System;
Vegetation Patterning in Semi-arid Environments;
Daisyworld: A Simple Land Surface Climate Model.

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Climate change is recognised as having potentially huge impacts on the environment and on human society. Read more
Climate change is recognised as having potentially huge impacts on the environment and on human society. This programme aims to provide an understanding of climate change causes, impacts, mitigation and adaptation measures from a life science perspective in conjunction with developing a wide variety of mathematical modelling skills that can be used to investigate the impacts of climate change.

The programme closely follows the structure of our Applied Mathematical Sciences MSc. Two of the mandatory courses will specifically focus on understanding the issues related to climate change and are taught by the School of Life Sciences.

Students will take a total of 8 courses, 4 in each of the 1st and 2nd Semesters followed by a 3-month Project in the summer. A typical distribution for this programme is as follows:

Core courses

Modelling and Tools;
Mathematical Ecology;
Climate Change: Causes and Impacts;
Climate Change: Mitigation and Adaptation Measures;
Dynamical Systems (recommended);
Stochastic Simulation (recommended)

Optional Courses

Optimization;
Mathematical Biology and Medicine;
Numerical Analysis of ODEs;
Applied Mathematics;
Statistical Methods;
Applied Linear Algebra;
Partial Differential Equations;
Numerical Analysis;
Geometry;
Bayesian Inference.

Typical project subjects

Population Cycles of Forest Insects;
Climate Change Impact;
The replacement of Red Squirrels by Grey Squirrels in the UK;
Vegetation Patterns in Semi-arid Environments;
Daisyworld: A Simple Land Surface Climate Model.

The final part of the MSc is an extended project in mathematical modelling the impacts of climate change on environmental systems, giving the opportunity to investigate a topic in some depth guided by leading research academics.

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Accurate and efficient scientific computations lie at the heart of most cross-discipline collaborations. It is key that such computations are performed in a stable, efficient manner and that the numerics converge to the true solutions, dynamics of the physics, chemistry or biology in the problem. Read more
Accurate and efficient scientific computations lie at the heart of most cross-discipline collaborations. It is key that such computations are performed in a stable, efficient manner and that the numerics converge to the true solutions, dynamics of the physics, chemistry or biology in the problem.

The programme closely follows the structure of our Applied Mathematical Sciences MSc and will equip you with the skill to perform efficient accurate computer simulations in a wide variety of applied mathematics, physics, chemical and industrial problems.

The MSc, has at its core, fundamental courses in pure mathematics and students will be able to take options from both pure and applied mathematics.

Students will take a total of 8 courses, 4 in each of the 1st and 2nd Semesters followed by a 3-month Project in the summer. A typical distribution for this programme is as follows:

Core courses

Modelling and Tools;
Functional Analysis;
Partial Differential Equations;
Pure Mathematics (recommended).

Optional Courses

Mathematical Ecology;
Optimization;
Numerical Analysis of ODEs;
Applied Mathematics;
Dynamical Systems;
Stochastic Simulation;
Applied Linear Algebra;
Partial Differential Equations;
Numerical Analysis;
Bayesian Inference and Computational Methods;
Geometry.

Typical project subjects

Domain Decomposition;
Mathematical Modelling of Crime;
The Geometry of Point Particles;
Can we Trust Eigenvalues on a Computer?;
Braess Paradox;
The Ising Model: Exact and Numerical Results;
Banach Alegbras.

The final part of the MSc is an extended project in computational mathematics, giving the opportunity to investigate a topic in some depth guided by leading research academics from our 5-rated mathematics and statistics groups.

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Accurate and efficient scientific computations lie at the heart of most cross-discipline collaborations. It is key that such computations are performed in a stable, efficient manner and that the numerics converge to the true solutions, dynamics of the physics, chemistry or biology in the problem. Read more
Accurate and efficient scientific computations lie at the heart of most cross-discipline collaborations. It is key that such computations are performed in a stable, efficient manner and that the numerics converge to the true solutions, dynamics of the physics, chemistry or biology in the problem.

The programme closely follows the structure of our Applied Mathematical Sciences MSc and will equip you with the skill to perform efficient accurate computer simulations in a wide variety of applied mathematics, physics, chemical and industrial problems.

Students will take a total of 8 courses, 4 in each of the 1st and 2nd Semesters followed by a 3-month Project in the summer. A typical distribution for this programme is as follows:

Core courses

Modelling and Tools;
Stochastic Simulation;
Applied Linear Algebra;
Numerical Analysis;

Optional Courses

Dynamical Systems;
Optimization;
Partial Differential Equations;
Numerical Analysis of ODEs;
Applied Mathematics;
Statistical Methods;
Functional Analysis;
Software Engineering Foundations;
Mathematical Biology and Medicine;
Biologically Inspired Computation;
Advanced Software Engineering;
Geometry;
Bayesian Inference;

Typical project subjects

Simulation of Granular Flow and Growing Sandpiles;
Finite Element Discretisation of ODEs and PDEs;
Domain Decomposition;
Computational Spectral Theory;
Mathematical Modelling of Crime;
Mathematical Modelling of Micro-electron Mechanical Systems.
Can we Trust Eigenvalues on a Computer?

The final part of the MSc is an extended project in computational mathematics, giving the opportunity to investigate a topic in some depth guided by leading research academics from our 5-rated mathematics and statistics groups.

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Food security is a complex issue of global significance and understanding the role and contribution of seafood within food security is an emerging research area. Read more

Introduction

Food security is a complex issue of global significance and understanding the role and contribution of seafood within food security is an emerging research area. Seafood products are provided by both aquaculture and capture fisheries and are one of the most highly traded food products globally. Including seafood in our daily diet provides an affordable source of macro and micronutrients required for optimal human health and development.
This course is designed to introduce the global issues affecting seafood production and trading, and will promote an understanding of the key factors affecting aquatic food production, post-harvest protocols, post-mortem metabolic events and microbial/chemical processes key for food safety and quality. Sensory assessment and shelf-life extension technologies will also be covered. The course will also examine other key issues in seafood trading such as traceability systems, certifications as well as the impact of governance and legislation on the global seafood sector.
This is the only aquatic food security MSc currently available in the UK. It will comprehensively follow the food chain from production through to consumer health and welfare.

Key information

- Degree type: MSc
- Study methods: Full-time
- Start date: September
- Course Director: Rachel Norman

English language requirements

If English is not your first language you must have one of the following qualifications as evidence of your English language skills:
- IELTS: 6.0 with 5.5 minimum in each skill
- Cambridge Certificate of Proficiency in English (CPE): Grade C
- Cambridge Certificate of Advanced English (CAE): Grade C
- Pearson Test of English (Academic): 54 with 51 in each component
- IBT TOEFL: 80 with no subtest less than 17

For more information go to English language requirements https://www.stir.ac.uk/study-in-the-uk/entry-requirements/english/

If you don’t meet the required score you may be able to register for one of our pre-sessional English courses. To register you must hold a conditional offer for your course and have an IELTS score 0.5 or 1.0 below the required standard. View the range of pre-sessional courses http://www.intohigher.com/uk/en-gb/our-centres/into-university-of-stirling/studying/our-courses/course-list/pre-sessional-english.aspx .

Structure and content

This course shares some modules with the MSc in Sustainable Aquaculture and there is flexibility within the system to change the degree title depending on what advanced modules are taken. The course is divided into four taught modules, containing 18 subject areas or topics, and a single Research Project module.

Delivery and assessment

In addition to lectures, tutorials and seminars, a number of assignments must be completed. Laboratory-based practical sessions are also important elements of the course. Taught module assessment is continuous, involving short tests, seminars, essays, practical reports, critical and computational analysis, field assignments and set project reports. The Research Project module is examined through written dissertation and seminar presentations by both supervisors and an external examiner.

Modes of study

The course is available on a block-release basis (by selecting individual or a series of modules) over a period not exceeding five academic years.

Why Stirling?

REF2014
In REF2014 Stirling was placed 6th in Scotland and 45th in the UK with almost three quarters of research activity rated either world-leading or internationally excellent.

Rating

The Institute of Aquaculture, with a rating of 2.45 in the latest Research Assessment Exercise (RAE), was graded the top aquaculture department in the UK.

Strengths

This MSc brings a unique perspective to the expertise that already exists in Stirling on global seafood production. It is the only MSc in the UK that focusses on how seafood can contribute to global food security.
We have a number of links in the production, processing and retail industries and this will provide students with the opportunity to interact with industry and potentially carry out a project which is of direct relevance to the sector.
We also have links within Asia and Europe which will allow the opportunity to undertake the Research Project overseas.

Academic strengths

The Institute of Aquaculture has been closely associated with the global expansion of aquaculture initially through developing and improving the existing production systems and the development of new farmed species. In recent years our research has focused on increasing the sustainability and reducing the environmental impact of these activities. In addition, we have recently invested in new posts in Aquatic Food Security whose activities also include research into food safety and quality post harvest, aquatic animal nutrition, as well as developing mathematical models of production systems. We therefore have expertise that covers the whole production cycle from farm to fork.
The Institute of Aquaculture is internationally recognised for both research and teaching and is one of only a handful of institutions devoted to aquatic food security. The goal is to develop and promote aquatic food security building on the Institute staff expertise in sustainable aquatic animal production.

Careers and employability

- Career opportunities
Demand for well qualified postgraduates to contribute to food production and the supply chain will continue to increase in line with demand to double food production over the coming decades. This course provides each student with the appropriate knowledge and practical experience important for a career in aquatic food security. The course has been developed to provide students with core knowledge and practical skills on aquaculture, food safety/quality, numerical analysis and legislation appropriate to aquatic food security. These skills will be equally applicable to those wishing to pursue an academic career as well as those seeking employment in Government or industry.

- Employability
This course has been developed to provide students with core knowledge and practical skills on aquaculture, food safety/quality, numerical analysis and legislation appropriate to aquatic food security. These skills will be equally applicable to those wishing to pursue an academic career as well as those seeking employment in Government or industry.

- Industry connections
We have a number of links in the production, processing and retail industries which provides students with the opportunity to interact with industry and potentially carry out a project which is of direct relevance to the sector. We also have links within Asia and Europe which allows the opportunity to undertake the research project overseas.

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The MPhil programme in Scientific Computing is a full-time 12-month course which aims to provide education of the highest quality at Master’s level. Read more
The MPhil programme in Scientific Computing is a full-time 12-month course which aims to provide education of the highest quality at Master’s level. Covering topics of high-performance scientific computing and advanced numerical methods and techniques, it produces graduates with rigorous research and analytical skills, who are well-equipped to proceed to doctoral research or directly into employment in industry, the professions, and the public service. It also provides training for the academic researchers and teachers of the future, encouraging the pursuit of research in computational methods for science and technology disciplines, thus being an important gateway for entering PhD programmes containing a substantial component of computational modelling.

See the website http://www.graduate.study.cam.ac.uk/courses/directory/pcphmpscm

Course detail

The MPhil in Scientific Computing has a research and a taught element. The research element is a project on a science or technology topic which is studied by means of scientific computation. The taught element comprises of core lecture courses on topics of scientific computing and elective lecture courses relevant to the science or technology topic of the project. Most of the projects are expected to make use of the University’s High Performance Computing Service.

The students will attend lecture courses during Michaelmas Term (some courses may be during Lent Term) and then they will undertake a substantial Research Project over the next 6 months (from March to the end of August) in a participating Department. The research element aims to provide essential skills for continuation to a PhD programme or employment, as well as to assess and enhance the research capacity of the students. It is based on a science or technology topic which is studied by means of scientific computation. Research project topics will be provided by academic supervisors or by the industrial partners who are working with the participating Departments and may be sponsoring the research project.

There is equal examination credit weighting between the taught and the research elements of the course, which is gained by submitting a dissertation on the project and by written assignments and examinations on the core and elective courses, respectively.

Weighting of the assessed course components is as follows: Dissertation (research) 50%; written assignments on the core courses 25%; written examinations on the elective courses 25%.

Learning Outcomes

By the end of the course, students will have:

- a comprehensive understanding of numerical methods, and a thorough knowledge of the literature, applicable to their own research;
- demonstrated originality in the application of knowledge, together with a practical understanding of how research and enquiry are used to create and interpret knowledge in their field;
- shown abilities in the critical evaluation of current research and research techniques and methodologies;
- demonstrated self-direction and originality in tackling and solving problems, and acted autonomously in the planning and implementation of research.

Format

The taught element comprises core lecture courses on topics of all aspects of scientific computing, and elective lecture courses relevant to the topic of the research project.

The taught element comprises core lecture courses on topics of all aspects of scientific computing, and elective lecture courses relevant to the topic of the research project. There is equal examination credit weighting between the taught and the research elements of the course, which is gained by submitting a dissertation on the project and by written assignments and examinations on the core and elective courses, respectively. Weighting of the assessed course components is as follows: Dissertation (research) 50%; written assignments 25%; written examinations 25%.

The core lectures are on topics of high performance scientific computing numerical analysis and advanced numerical methods and techniques. They are organized by the Centre for Scientific Computing and are taught and examined during the first five months (October-February). Their purpose is to provide the students with essential background knowledge for completing their dissertation and for their general education in scientific computing.

In particular, their objective is to introduce students to the simulation science pipeline of problem identification, modelling, simulation and evaluation - all from the perspective of employing high-performance computing. Numerical discretisation of mathematical models will be a priority, with a specific emphasis on understanding the trade-offs (in terms of modelling time, pre-processing time, computational time, and post-processing time) that must be made when solving realistic science and engineering problems. Understanding and working with computational methods and parallel computing will be a high priority. To help the students understand the material, the lecturers will furnish the courses with practical coursework assignments.

The lectures on topics of numerical analysis and HPC are complemented with hands-on practicals using Linux-based laptops provided by the course (students may bring their own), as well as on the University’s High Performance Computing Service.

Appropriate elective lecture courses are selected from Master’s-level courses offered by the Departments of the School of Physical Sciences, Technology or Biological Sciences. The choice of courses will be such as to provide the students with essential background knowledge for completing their theses and for their general education in the materials science application of the project. They are decided in consultation with the project supervisor. While every effort is made within the Departments to arrange the timetable in a coherent fashion, it is inevitable that some combinations of courses will be ruled out by their schedule, particularly if the choices span more than one department.

Continuing

For continuation to a PhD programme in Scientific Computing, students are required to gain a Distinction (overall grade equal or greater than 75%).

How to apply: http://www.graduate.study.cam.ac.uk/applying

Funding Opportunities

There are no specific funding opportunities advertised for this course. For information on more general funding opportunities, please follow the link below.

General Funding Opportunities http://www.graduate.study.cam.ac.uk/finance/funding

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This programme is designed to directly improve the employment prospects of graduates by teaching key functional business knowledge and skills. Read more
This programme is designed to directly improve the employment prospects of graduates by teaching key functional business knowledge and skills. Especially suitable for those seeking careers as business analysts or management consultants, students are trained in the core aspects of business management with particular emphasis on the development of a range of business modelling, data analysis and consultancy skills.

Students will gain the foundational knowledge needed to perform effectively a set of key business analysis functions.

The programme content has been tailored from the research areas and specialisms of our world-renowned staff, meaning our students not only experience the very best teaching quality, but also graduate with the capability to contribute quickly and purposefully to the running of any organisation.

There is also a strategic theme within the programme to instil knowledge and skills relevant to middle management and to more senior roles for later in your career. Our modules use contemporary case studies and skills-based coursework, ensuring that our graduates can apply up-to-date and relevant knowledge to a range of business situations.

Core study areas include accounting and financial management, human resource management, marketing in the organisation, operations management, business forecasting, operational research methods, business analysis and planning, global strategic management, and skills for employability and personal development.

See the website http://www.lboro.ac.uk/study/postgraduate/programmes/departments/business-economics/business-analysis-management/

Programme modules

Semester 1:
Compulsory Modules
- Accounting and Financial Management
- Human Resource Management
- Marketing Management
- Operations Management

Semester 2:
Compulsory Modules
- Business Forecasting
- Operational Research Methods
- Information Systems and Management

Optional Modules* (choose two)
- Business Economics
- Enterprise, Employability and Personal Development
- Enterprise Resource Planning
- Global Outsourcing and Offshoring of Services
- International Business Environment
- International Marketing
- Logistics and Supply Chain Management
- Services and Retail Management
- Small Business and Entrepreneurship
- Work Psychology

* Other optional modules are available

Summer:
- Business Analysis and Planning
- Strategic Management

Assessment

Modules are assessed by a combination of examinations and assignments.

Careers and further study

Example destinations include:
BAE Systems – Finance Graduate Scheme; Marks & Spencer – Forecast Planner; Nomura – Client Information Analyst; Logica – Analyst; INES Research – Research Analyst.

Why choose business and economics at Loughborough?

Loughborough’s School of Business and Economics is a thriving forward-looking centre of education that aims to provide an exceptional learning experience.

Consistently ranked as a Top-10 UK business school by national league tables, our graduates are highly employable and enjoy starting salaries well above the national average.

The rich variety of postgraduate programmes we offer ranges from taught masters, MBA and doctoral programmes, to short courses and executive education, with subjects spanning Management, Marketing, Finance and Economics, Work Psychology, Business Analytics, International Crisis Management and Information Management. New for 2016, we are also launching two exciting new programmes in Human Resource Management. All of this contributes to a lively and supportive learning environment within the School.

- Internationally Accredited
The School of Business and Economics is one of less than 1% of business schools in the world to have achieved accreditation from all three major international accrediting bodies: The Association to Advance Collegiate Schools of Business (AACSB International), EQUIS accreditation from the European Foundation for Management Development (EFMD) and the Association of MBAs (AMBA).

- Career Prospects
Our graduates are in great demand. Over 94% of our postgraduate students were in work and/or further study six months after graduating.* As such, you will be equipped with skills and knowledge that will serve you well in your career or enable you to pursue further study and research.

*Source: DLHE

Find out how to apply here http://www.lboro.ac.uk/study/postgraduate/programmes/departments/business-economics/business-analysis-management/

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Most business schools offer an MSc in Finance. Few offer an MSc with such a strong investment component. A powerful blend of academic rigour and vocational insight, the MSc in Finance and Investment will add considerably to the knowledge of those looking to further their career in this vital sector. Read more

This programme is not currently accepting applications.

Programme description

Most business schools offer an MSc in Finance. Few offer an MSc with such a strong investment component. A powerful blend of academic rigour and vocational insight, the MSc in Finance and Investment will add considerably to the knowledge of those looking to further their career in this vital sector.

The School's location in the UK's second largest financial centre allows us to attract visiting speakers from the key financial institutions, fund management houses and a range of analysts. Students are able to interact with leading figures from many major companies; this is particularly evident in the dissertation, which offers an invaluable opportunity to collaborate on a topic that has real, of-the-minute industry relevance.

The practical, theoretical and numerical skills learnt through the programme, as well as the global perspective of investment markets and asset classes, will leave you well qualified for a range of finance related professions. We expect graduates to take up positions in investment analysis, portfolio management, financial statement analysis and evaluation, corporate finance, product development, client servicing and risk management.

The School is recognised a partner institution by the Chartered Financial Analysis (CFA) Institute. Equally the School is recognised as a Centre of Excellence in the provision of postgraduate education in finance and investment by the Chartered Institute for Securities & Investment (CISI).

Programme structure

Learning will primarily be through lectures, set reading, class discussions, exercises, group-work assignments, problem solving in tutorials and case studies. Assessment methods include examinations, assignments, presentations or continuous assessment.

Learning outcomes

Students will learn about corporate finance, global financial markets, financial accounting statements, derivatives, portfolio management, investment analysis and investment mathematics. They will also learn about the use of software and sources of information in investment and risk management.

How to estimate the fair value for an investment, to test assumptions and sensitivities and to compare different investments are explored in depth. Students will also gain an understanding of the role of different asset classes, their behaviour in isolation and in relation to other asset classes, and an understanding of how portfolios of investments can be constructed and analysed.

Intellectual skills

Students will develop:

critical analysis – an ability to assimilate new knowledge in the field of finance and investment (and to analyse the information gained) and the operations and methods used in the financial sector
research skills – an ability to identify and define pertinent research questions, to review the relevant literature, to define a proper methodology and to conduct research in the context of data analysis or other suitable methods
discipline – a major difficulty in investment is removing emotion from the decision-making process; research in behavioural finance shows that the desire of investors to follow consensus, and the ease with which they can misinterpret data, are obstacles to sound decision making - the programme will seek to imbue students with the discipline required to make good investment decisions
analytical and numerical skills – an ability to analyse and solve investment problems, to handle large volumes of numerical data, to extract and manipulate relevant data in a meaningful manner, and to analyse accounting information

Subject-specific knowledge

Students will develop:

an understanding of investment and risk-management tools and databases such as Datastream, Osiris, WRDS and ThomsonOne Banker, through use of such products and demonstrations of their output and capabilities
an understanding of industry practice in risk management and general techniques such as value-at-risk and optimisation
an ability to understand, speak and write the language of finance and investment. An ability to analyse financial statements of companies, to evaluate earnings quality and firm performance
an understanding of analytical and problem-solving methods through the use of techniques such as discounted cash flow analysis, quadratic programming, sensitivity analysis, scenario analysis and Monte Carlo Simulation
an understanding of risk and its applicability beyond investment
a knowledge of the nature and findings of academic enquiry in the areas of finance and investment

Transferable skills

Students will develop an:

ability to understand, assess and present complex lines of argument
ability to work individually and with others in teams, often under time pressure
ability to communicate clearly on paper and in presentations
enhanced numerical skills and fluency in spreadsheet use, developed through problem solving in quantitative courses within the programme

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This course focuses on the physical processes that generate natural hazards through an advanced understanding of geological and environmental processes. Read more

Why take this course?

This course focuses on the physical processes that generate natural hazards through an advanced understanding of geological and environmental processes.

You will be fully trained by internationally recognised experts in hazard identification, terrain evaluation techniques as well as hazard modelling and risk assessment techniques. Providing you with the essential skills to monitor, warn and help control the consequences of natural hazards.

What opportunities might it lead to?

This course is accredited by the Geological Society of London. It offers advanced professional and scientific training providing an accelerated route for you to attain Chartered Status, such as Chartered Geologist (CGeol) and Chartered Scientist (CSci) on graduation.

Here are some routes our graduates have pursued:

Aid organisations
Environmental organisations
Offshore work
Civil sector roles
Mining
Insurance companies

Module Details

You can opt to take this course in full-time or part-time mode.

The course is divided into two parts. The first part comprises the lecture, workshop, practical and field work elements of the course, followed by a five-month independent research project. The course is a mixture of taught units and research project covering topics including site investigation, hazard modelling and mapping, soil mechanics and rock mechanics, contaminated land, flooding and slope stability.

Here are the units you will study:

Natural Hazard Processes: The topic of this unit forms the backbone of the course and give you an advanced knowledge of a broad range of geological and environmental hazards, including floods, landslides, collapsible ground, volcanoes, earthquakes, tsunamis, hydro-meteorological and anthropogenic hazards. External speakers are used to provide insights and expertise from an industry, regulatory and research perspective.

Numerical Hazard Modelling and Simulation: This forms an important part of the course, whereby you are trained in the application of computer models to the simulation of a range of geological and environmental hazards. You will develop skills in computer programming languages and use them to develop numerical models that are then used to simulate different natural hazard scenarios.

Catastrophe Modelling: On this unit you will cover the application of natural hazard modelling to better understand the insurance sector exposure to a range of geological and environmental hazards. It includes external speakers and sessions on the application of models for this type of catastrophe modelling.

Volcanology and Seismology: You will gain an in-depth knowledge of the nature of volcanism and associated hazards and seismology, associated seismo-tectonics and earthquake hazards. This unit is underpinned by a residential field course in the Mediterranean region that examines the field expression of volcanic, seismic and other natural hazards.

Flooding and Hydrological Hazards: These are a significant global problem that affect urban environments, one that is likely to increase with climate change. This unit will give you an in-depth background to these hazards and opportunities to simulate flooding in order to model the flood hazard and calculate the risk.

Hazard and Risk Assessment: This unit gives you the chance to study the techniques that are employed once a hazard has been identified and its likely impact needs to be measured. You will have advanced training in the application of qualitative and quantitative approaches to hazard and risk assessment and their use in the study of different natural hazards.

Field Reconnaissance and Geomorphological Mapping: These techniques are integral to the course and an essential skill for any graduate wishing to work in this area of natural hazard assessment. On this unit you will have fieldwork training in hazard recognition using techniques such as geomorphological mapping and walk-over surveys, combined with interpretation of remote sensing and aerial photography imagery.

Spatial Analysis and Remote Sensing: You will learn how to acquire and interpret aerial photography and satellite imagery, and the integration and analysis of spatial datasets using GIS – all key tools for hazard specialists.

Geo-mechanical Behaviour of Earth Materials: You will train in geotechnical testing and description of soils and rocks to the British and international standards used by industry.

Landslides and Slope Instability: This unit will give you an advanced understanding of landslide systems, types of slides in soils and rocks and methods for identification and numerical analysis.

Impacts and Remediation of Natural Hazards: You will cover a growing area of study, including the impact of hazardous events on society and the environment, and potential mitigation and remediation methods that can be employed.

Independent Research Project: This provides you with an opportunity to undertake an original piece of research to academic or industrial standards, typically in collaboration with research staff in the department or external industry partners. In addition to submission of a thesis report, you also present the results of your project at the annual postgraduate conference held at the end of September.

Programme Assessment

The course provides a balanced structure of lectures, seminars, tutorials and workshops. You will learn through hands-on practical sessions designed to give you the skills in laboratory, computer and field techniques. The course also includes extensive field work designed to provide field mapping and data collection skills.

Assessment is varied, aimed at developing skills relevant to a range of working environments. Here’s how we assess your work:

Poster and oral presentations
Project reports
Literature reviews
Lab reports
Essays

Student Destinations

This course provides vocational skills designed to enable you to enter this specialist environmental field. These skills include field mapping, report writing, meeting deadlines, team working, presentation skills, advanced data modelling and communication.

You will be fully equipped to gain employment in the insurance industry, government agencies and specialist geoscience companies, all of which are tasked with identifying and dealing with natural hazards. Previous destinations of our graduates have included major re-insurance companies, geological and geotechnical consultancies, local government and government agencies.

It also has strong research and analytical components, ideal if you wish to pursue further research to PhD level.

We aim to provide you with as much support as possible in finding employment through close industrial contacts, careers events, recruitment fairs and individual advice.

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Engineering geological expertise is critical to all types of civil engineering projects such as tunnels, dams, mines, quarries, offshore platforms and wind farms. Read more

Why take this course?

Engineering geological expertise is critical to all types of civil engineering projects such as tunnels, dams, mines, quarries, offshore platforms and wind farms.

This course provides you with the advanced skills to carry out detailed investigations into surface and subsurface geology, identification of adverse ground conditions and the design of suitable remedial measures of engineering structures.

What will I experience?

On this course you can:

Be taught by internationally recognised experts with extensive expertise in engineering geology and geotechnics
Gain experience of environmental assessment techniques, plus a range of other skills such as mapping using GIS, GPS and remote sensing technologies
Go on numerous fieldtrips, both locally and overseas, to undergo specialist field training

What opportunities might it lead to?

This course is accredited by the Geological Society of London. It offers advanced professional and scientific training providing an accelerated route for you to attain Chartered Status, such as Chartered Geologist (CGeol) and Chartered Scientist (CSci) on graduation.

Here are some routes our graduates have pursued:

Aid organisations
Environmental organisations
Offshore work
Civil sector roles
Mining
Insurance companies

Module Details

You can opt to take this course in full-time or part-time mode.

The course is divided into two parts. The first part comprises of the lecture, workshop, practical and field work elements of the course, followed by a five-month independent research project. The course is a mixture of taught units and research project covering topics including site investigation, soil mechanics and rock mechanics, geotechnical engineering design, contaminated land, slope stability and rock engineering.

Here are the units you will study:

Rock and Soil Mechanics: These topics are integral to the role of an engineering geologist. You will gain an advanced understanding of the geo-mechanical behaviour of rocks and soils and how they behave under different geotechnical design scenarios. You will also develop key skills in the assessment, description and testing of geological materials in order to understand and quantify their behaviour, using current British and Eurocode standards.

Soil and Rock Engineering: This unit will give you an advanced understanding of engineering and design in soils and rock masses, including fundamental design principles associated with common geotechnical solutions encountered on engineering geological and civil engineering projects.

Contaminated Land and Groundwater: These are important considerations in all types of construction and so an understanding of both is essential. You will learn key techniques for the identification and assessment of contaminated land and groundwater resources in an engineering geological context.

Ground Models: You will train in the development of geological ground models and geomorphological terrain models within the content of engineering geological practice, essential parts of any investigation.

Ground Investigation Techniques: You will gain advanced experience of ground investigation using invasive techniques, in-situ tests and geophysical methods – essential to an engineering geologist's skill base.

Landslides and Slope Instability: On this unit you will develop an advanced understanding of landslide systems, types of slides in soils and rocks and methods for identification and numerical analysis.

Field Reconnaissance and Geomorphological Mapping: The techniques covered on this unit are integral to the course and an essential skill for any graduate wishing to work in this area. You will have fieldwork training in techniques such as geomorphological mapping and walk-over surveys combined with interpretation of remote sensing and aerial photography imagery.

Spatial Analysis and Remote Sensing: On this unit you will cover the key tools for terrain evaluation and be trained in the acquisition and interpretation of aerial photography and satellite imagery, and the integration and analysis of spatial datasets using GIS.

Independent Research Project: This give you the opportunity to undertake an original piece of research to academic or industrial standards, typically in collaboration with research staff in the department or external industry partners. In addition to submission of a thesis report, you also present the results of your project at the annual postgraduate conference held at the end of September.

Programme Assessment

The course provides a balanced structure of lectures, seminars, tutorials and workshops. You will learn through hands-on practical sessions designed to give you the skills in laboratory, computer and field techniques. The course also includes extensive field work designed to provide field mapping and data collection skills.

Assessment is varied, aimed at developing skills relevant to a range of working environments. Here’s how we assess your work:

Poster and oral presentations
Project reports
Literature reviews
Lab reports
Essays

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Take advantage of one of our 100 Master’s Scholarships or College of Science Postgraduate Scholarships to study Mathematics and Computing for Finance at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Read more
Take advantage of one of our 100 Master’s Scholarships or College of Science Postgraduate Scholarships to study Mathematics and Computing for Finance at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Postgraduate loans are also available to English and Welsh domiciled students. For more information on fees and funding please visit our website.

The MSc Mathematics and Computing for Finance course has been designed to meet the growing demand for specially trained mathematicians to work in the world’s financial markets and insurance.

Despite the current volatile nature of the banking industry, many banks still have a pressing need for employees with advanced mathematical skills who can further their understanding of turbulence in financial markets.

On the Mathematics and Computing for Finance course you will study different elements of both mathematics and computing in addition to developing your communication and presentational skills through a project you will undertake. As a student of the MSc in Mathematics and Computing for Finance programme you will be fully supported to ensure that your project is best suited to support your future career plans.

Aims of MSc in Mathematics and Computing for Finance

Have in depth knowledge in stochastic analysis and parts of advanced real analysis. (Fourier analysis and Partial Differential Equations) as well as parts of numerical analysis which are central for applications to finance.

Have developed advanced computing skills being essential for handling problems relevant for a job on the finance markets.

Have, as a mathematician, a good understanding of finance markets.

Have developed skills needed to work in a highly inter-disciplinary profession, including advanced programming techniques and communication skills across the borders.

Modules

Please visit our website for a full description of modules for the MSc Mathematics and Computing for Finance.

Careers

The ability to think rationally and to process data clearly and accurately are highly valued by employers. Mathematics graduates earn on average 50% more than most other graduates. The most popular areas are the actuarial profession, the financial sector, IT, computer programming and systems administration, and opportunities within business and industry where employers need mathematicians for research and development, statistically analysis, marketing and sales.

Some of our students have been employed by AXA, BA, Deutsche Bank, Shell Research, Health Authorities and Local Government. Teaching is another area where maths graduates will find plenty of career opportunities.

Research

The results of the Research Excellence Framework (REF) 2014 show that our research environment (how the Department supports research staff and students) and the impact of our research (its value to society) were both judged to be 100% world leading or internationally excellent.

All academic staff in Mathematics are active researchers and the department has a thriving research culture.

Student profiles

"Further to my studies at Swansea University as a Master of Science graduate in Financial Mathematics, I am currently working at Deutsche Bank in London as part of the Structured Financial Services team providing client services for corporate lending and debt portfolios. The complex nature of the course has helped me become a logical decision maker and a highly skilled problem solver. These transferable skills are very useful in the world of Finance since the role is highly challenging working towards deadlines and structured transaction targets. My studies at Swansea University have also enriched me with leadership, motivational skills and have enhanced my communication skills. I work in a close team of 10 people within a large department which encourages a culture that strives towards learning and effective teamwork. I thoroughly enjoyed my time at Swansea University and cherish the many fond memories. I am so pleased to be expanding my horizon within a major financial centre."

Rhian Ivey, BSc Mathematics, MSc Mathematics and Computing for Finance

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The University of Dundee has a long history of mathematical biology, going back to Professor Sir D'Arcy Wentworth Thompson, Chair of Natural History, 1884-1917. Read more

Mathematical Biology at Dundee

The University of Dundee has a long history of mathematical biology, going back to Professor Sir D'Arcy Wentworth Thompson, Chair of Natural History, 1884-1917. In his famous book On Growth and Form (where he applied geometric principles to morphological problems) Thompson declares:

"Cell and tissue, shell and bone, leaf and flower, are so many portions of matter, and it is in obedience to the laws of physics that their particles have been moved, molded and conformed. They are no exceptions to the rule that God always geometrizes. Their problems of form are in the first instance mathematical problems, their problems of growth are essentially physical problems, and the morphologist is, ipso facto, a student of physical science."

Current mathematical biology research in Dundee continues in the spirit of D'Arcy Thompson with the application of modern applied mathematics and computational modelling to a range of biological processes involving many different but inter-connected phenomena that occur at different spatial and temporal scales. Specific areas of application are to cancer growth and treatment, ecological models, fungal growth and biofilms. The overall common theme of all the mathematical biology research may be termed"multi-scale mathematical modelling" or, from a biological perspective, "quantitative systems biology" or"quantitative integrative biology".

The Mathematical Biology Research Group currently consists of Professor Mark Chaplain, Dr. Fordyce Davidson and Dr. Paul Macklin along with post-doctoral research assistants and PhD students. Professor Ping Lin provides expertise in the area of computational numerical analysis. The group will shortly be augmented by the arrival of a new Chair in Mathematical Biology (a joint Mathematics/Life Sciences appointment).

As a result, the students will benefit directly not only from the scientific expertise of the above internationally recognized researchers, but also through a wide-range of research activities such as journal clubs and research seminars.

Aims of the programme

1. To provide a Masters-level postgraduate education in the knowledge, skills and understanding of mathematical biology.
2. To enhance analytical and critical abilities and competence in the application of mathematical modeling techniques to problems in biomedicine.

Prramme Content

This one year course involves taking four taught modules in semester 1 (September-December), followed by a further 4 taught modules in semester 2 (January-May), and undertaking a project over the Summer (May-August).

A typical selection of taught modules would be:

Dynamical Systems
Computational Modelling
Statistics & Stochastic Models
Inverse Problems
Mathematical Oncology
Mathematical Ecology & Epidemiology
Mathematical Physiology
Personal Transferable Skills

Finally, all students will undertake a Personal Research Project under the supervision of a member of staff in the Mathematical Biology Research Group.

Methods of Teaching

The programme will involve a variety of teaching formats including lectures, tutorials, seminars, journal clubs, case studies, coursework, and an individual research project.

Taught sessions will be supported by individual reading and study.

Students will be guided to prepare their research project plan and to develop skills and competence in research including project management, critical thinking and problem solving, project reporting and presentation.

Career Prospects

The Biomedical Sciences are now recognizing the need for quantitative, predictive approaches to their traditional qualitative subject areas. Healthcare and Biotechnology are still fast-growing industries in UK, Europe and Worldwide. New start-up companies and large-scale government investment are also opening up employment prospects in emerging economies such as Singapore, China and India.

Students graduating from this programme would be very well placed to take advantage of these global opportunities.

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The MSc in Quantitative Finance develops sophisticated statistical, programming and economic skills for roles in areas such as quantitative asset management and risk management. Read more
The MSc in Quantitative Finance develops sophisticated statistical, programming and economic skills for roles in areas such as quantitative asset management and risk management.

The MSc in Quantitative Finance will equip you with a rigorous understanding of the theory behind asset pricing, fixed income securities and risk management, supported by solid knowledge of numerical analysis and programming languages; special emphasis is on econometric techniques as forecasting and market microstructure analysis.

Typical career paths of graduates from our MSc in Quantitative Finance include research positions (in both financial and academic institutions), or roles involving the assessment of market microstructure across a number of exchanges, stress testing/scenario analysis, development and improvements of asset allocation models and analysis of potential investment vehicles across different asset classes, such as Hedge Funds Risk Analyst, Financial Analyst and Asset Allocation Analyst.

The demand for recruits with strong quantitative skills has spread beyond the pure derivatives area, and graduates from the course move into a range of careers in the financial sector. Cass's proximity to the City of London helps graduates to access outstanding career opportunities, especially as Cass has close links with many City institutions.

Visit the website: http://www.cass.city.ac.uk/courses/masters/courses/quantitative-finance

Course detail

There are two Induction Weeks The Quantitative Finance course starts with two compulsory induction weeks, focused on:

• an introduction to careers in finance and the opportunity to speak to representatives from over 75 companies during a number of different industry specific fairs.

• a reminder course of advanced financial mathematics, statistics and basic computing which forms a prerequisite of the core modules in term 1.

Format

To satisfy the requirements of the degree programme students must complete:

• eight core courses (15 credits each)
and
• two additional core modules plus three electives (10 credits each)
or
• three electives (10 credits each) and an Applied Research Project (20 credits)
or
• one elective (10 credits) and a Business Research Project (40 credits)

Assessment

Assessment of modules on the MSc in Quantitative Finance, in most cases, is by means of coursework and unseen examination. Coursework may consist of standard essays, individual and group presentations, group reports, classwork, unseen tests and problem sets. Please note that any group work may include an element of peer assessment.

Career opportunities

Although investment and hedge funds remain the biggest users and innovators in quantitative finance, other financial sectors such as commercial banking, insurance and fund management are now keenly interested. Fund managers and hedge funds, for example, make extensive use of quantitative techniques to develop trading strategies, optimise portfolios and assess risk.

Some examples of where graduates from the MSc in Quantitative Finance class of 2014 are working are:

• Capita Asset Services - Analyst
• RBS - Graduate Risk Analyst
• Dong MeKong Construction Manufacture and Trading - Project Assistant
• nPOWER - Quant Risk Analyst

How to apply

Apply here: http://www.city.ac.uk/study/postgraduate/applying-to-city

Funding

For information on funding, please follow this link: http://www.city.ac.uk/study/postgraduate/funding-and-financial-support

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