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Masters Degrees (Probability)

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The MSc Statistics and Applied Probability is suitable for students who wish to broaden and deepen their knowledge in both statistics and applied probability. Read more

Overview

The MSc Statistics and Applied Probability is suitable for students who wish to broaden and deepen their knowledge in both statistics and applied probability.

The course offers you the opportunity to further your knowledge in both of these areas, which will be beneficial for a professional career in statistics or as a solid basis for research in statistics or applied probability.

Topics include advanced stochastic processes, queueing processes, epidemic models and reliability, as well as most of those listed for the MSc Statistics.

This course is accredited by the Royal Statistical Society

Key facts:
- This course is informed by the work being carried out in the Statistics and Probability research group.
- The School of Mathematical Sciences is one of the largest and strongest mathematics departments in the UK, with over 50 full-time academic staff.
- In the latest independent Research Assessment Exercise, the School ranked 8th in the UK in "research power" across the three subject areas within the School of Mathematical Sciences (Pure Mathematics, Applied Mathematics, Statistics and Operational Research).
- This course is accredited by the Royal Statistical Society.

Modules

Advanced Stochastic Processes

Applications of Statistics

Computational Statistics

Fundamentals of Statistics

Medical Statistics

Statistics Dissertation

Time Series and Forecasting

Topics in Biomedical Statistics

English language requirements for international students

IELTS: 6.0 (with no less than 5.5 in any element)

Further information



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High-level training in statistics and the modelling of random processes for applications in science, business or health care. Read more

High-level training in statistics and the modelling of random processes for applications in science, business or health care.

For many complex systems in nature and society, stochastics can be used to efficiently describe the randomness present in all these systems, thereby giving the data greater explanatory and predictive power. Examples include statistical mechanics, financial markets, mobile phone networks, and operations research problems. The Master’s specialisation in Applied Stochastics will train you to become a mathematician that can help both scientists and businessmen make better decisions, conclusions and predictions. You’ll be able to bring clarity to the accumulating information overload they receive.

The members of the Applied Stochastics group have ample experience with the pure mathematical side of stochastics. This area provides powerful techniques in functional analysis, partial differential equations, geometry of metric spaces and number theory, for example. The group also often gives advice to both their academic colleagues, and organisations outside of academia. They will therefore not only be able to teach you the theoretical basis you need to solve real world stochastics problems, but also to help you develop the communications skills and professional expertise to cooperate with people from outside of mathematics.

See the website http://www.ru.nl/masters/mathematics/stochastics

Why study Applied Stochastics at Radboud University?

- This specialisation focuses both on theoretical and applied topics. It’s your choice whether you want to specialise in pure theoretical research or perform an internship in a company setting.

- Mathematicians at Radboud University are expanding their knowledge of random graphs and networks, which can be applied in the ever-growing fields of distribution systems, mobile phone networks and social networks.

- In a unique and interesting collaboration with Radboudumc, stochastics students can help researchers at the hospital with very challenging statistical questions.

- Because the Netherlands is known for its expertise in the field of stochastics, it offers a great atmosphere to study this field. And with the existence of the Mastermath programme, you can follow the best mathematics courses in the country, regardless of the university that offers them.

- Teaching takes place in a stimulating, collegial setting with small groups. This ensures that you’ll get plenty of one-on-one time with your thesis supervisor at Radboud University .

- More than 85% of our graduates find a job or a gain a PhD position within a few months of graduating.

Career prospects

Master's programme in Mathematics

Mathematicians are needed in all industries, including the banking, technology and service industries, to name a few. A Master’s in Mathematics will show prospective employers that you have perseverance, patience and an eye for detail as well as a high level of analytical and problem-solving skills.

Job positions

The skills learned during your Master’s will help you find jobs even in areas where your specialised mathematical knowledge may initially not seem very relevant. This makes your job opportunities very broad and is the reason why many graduates of a Master’s in Mathematics find work very quickly.

Possible careers for mathematicians include:

- Researcher (at research centres or within corporations)

- Teacher (at all levels from middle school to university)

- Risk model validator

- Consultant

- ICT developer / software developer

- Policy maker

- Analyst

PhD positions

Radboud University annually has a few PhD positions for graduates of a Master’s in Mathematics. A substantial part of our students attain PhD positions, not just at Radboud University, but at universities all over the world.

Our research in this field

The research of members of the Applied Stochastics Department, focuses on combinatorics, (quantum) probability and mathematical statistics. Below, a small sample of the research our members pursue.

Eric Cator’s research has two main themes, probability and statistics.

1. In probability, he works on interacting particles systems, random polymers and last passage percolation. He has also recently begun working on epidemic models on finite graphs.

2. In statistics, he works on problems arising in mathematical statistics, for example in deconvolution problems, the CAR assumption and more recently on the local minimax property of least squares estimators.

Cator also works on more applied problems, usually in collaboration with people from outside statistics, for example on case reserving for insurance companies or airplane maintenance. He has a history of changing subjects: “I like to work on any problem that takes my fancy, so this description might be outdated very quickly!”

Hans Maassen researches quantum probability or non-commutative probability, which concerns a generalisation of probability theory that is broad enough to contain quantum mechanics. He takes part in the Geometry and Quantum Theory (GQT) research cluster of connected universities in the Netherlands. In collaboration with Burkhard Kümmerer he is also developing the theory of quantum Markov chains, their asymptotic completeness and ergodic theory, with applications to quantum optics. Their focal point is shifting towards quantum information and control theory, an area which is rapidly becoming relevant to experimental physicists.

Ross Kang conducts research in probabilistic and extremal combinatorics, with emphasis on graphs (which abstractly represent networks). He works in random graph theory (the study of stochastic models of networks) and often uses the probabilistic method. This involves applying probabilistic tools to shed light on extremes of large-scale behaviour in graphs and other combinatorial structures. He has focused a lot on graph colouring, an old and popular subject made famous by the Four Colour Theorem (erstwhile Conjecture).

See the website http://www.ru.nl/masters/mathematics/stochastics

Radboud University Master's Open Day 10 March 2018



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This programme is now closed but you may want to consider other courses such as the . Mathematics MSc. . . Read more

This programme is now closed but you may want to consider other courses such as the Mathematics MSc

The Financial Mathematics MSc programme enables graduates and professionals with a strong mathematical background to research, develop and apply quantitative and computational techniques to investment and risk management. Based in the Department of Mathematics, this course has a superb reputation for research-led teaching and strong links to industry.

  • A rigorous approach to quantitative finance taught entirely by the Department of Mathematics.
  • In-depth coverage of the skills needed for working in the financial, actuarial or related industry: probability theory, optimisation, statistics and computer implementation.
  • Unrivalled facilities in central London with City of London's financial centre close by, and with access to live market data in our Bloomberg Data Laboratory.
  • Flexible study programme offering the opportunity to study part-time.
  • King’s is a member of the London Graduate School in Mathematical Finance which provides advanced courses for students who wish to push beyond the MSc core syllabus.
  • Lecturers on the programme have extensive experience in consulting and work for financial companies and institutions such as Bank of Finland, Commerzbank, Deutsche Bank, Goldman Sachs, ION Trading, Standard Chartered Bank and Winton Capital Management.

Description

Financial Mathematics studies problems of optimal investment and risk management, and this course covers a diverse range of topics, from classical options pricing to post-crisis investment and risk management

Like any branch of applied mathematics, financial mathematics analyses a given problem by first building a mathematical model for it and then examining the model. Both steps require detailed knowledge in different areas of mathematics, including probability, statistics, optimisation, computer science and many more traditional fields of mathematics.

Our Financial Mathematics MSc course is a unique study pathway that encompasses the essential skills required for successful risk management, trading and research in quantitative finance: probability, statistics, optimisation, computing and financial markets. You will explore probability theories, risk neutral valuation, stochastic analysis as well as interest rate and credit risk modules. We also offer you the opportunity to study an additional zero-credit supportive module called mathematical analysis for financial mathematics.

The Financial Mathematics MSc programme offers you the choice to study either full or part-time and is made up of optional and required modules. You must take modules totalling 180 credits to complete the course. If you are studying full-time, you will complete the course in one year, from September to September. If you are studying part-time, your programme will take two years to complete, you will study the required modules in the first year, and a further selection of required and optional modules including the 60-credit financial mathematics report module in your second year.

Bloomberg terminal laboratory

King’s is one of only a few academic departments in the UK that offers full access to Bloomberg terminals. These terminals will provide you access to live financial data. They are heavily used within the financial industry, and the data they provide is critical in assisting traders in making investment decisions and for risk managers monitoring investment probabilities. We have 13 Bloomberg terminals available for exclusive use by the Financial Mathematics MSc programme.

You will use the Bloomberg terminals to:

  • Gain an intuition for the conduct of real financial markets
  • Develop potential investment strategies
  • Experience using real-world investment and risk management software and obtain data for research.

The skills you will learn from using the terminals are highly valued by employers. King’s is part of a strong network of financial mathematics in London with connections both in academia and in the industry.

We are also members of the University of London and by arrangement, you can enrol in optional modules at other institutions within the University of London, which includes Birkbeck, London School of Economics and Political Sciences, University College London and many others.

Course purpose

This programme is suitable for students or professionals with a strong mathematical background. It covers the principles and techniques of quantitative finance to prepare students for advanced work in the financial sector or research in mathematical finance.

Course format and assessment

Teaching

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

Average per week: Three hours for 11 weeks per each 15 credit module.

You are expected to spend approximately 10 hours of effort for each credit (so for a typical module of 15 credits this means 150 hours of effort).

Assessment

The primary method of assessment for this course is a combination of written examinations, essays, coursework and individual or group projects and oral presentations.  

Career destinations

Our graduates are highly sought after by investment banks, corporate risk management units, insurance companies, fund management institutions, financial regulatory bodies, brokerage firms, and trading companies. Recent employers of our graduates include, Capital Investment, Credit Suisse, European Bank for Reconstruction & Development, Fitch Ratings, HSBC and Morgan & Stanley. Some graduates have pursued research degrees in financial mathematics.



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You can study this Mathematical Sciences MSc programme full-time or part-time. It offers students the opportunity to specialise in a broad range of areas across pure and applied mathematics, statistics and probability, and theoretical physics. Read more
You can study this Mathematical Sciences MSc programme full-time or part-time. It offers students the opportunity to specialise in a broad range of areas across pure and applied mathematics, statistics and probability, and theoretical physics.

The topics we cover include:

- advanced probability theory
- algebra
- asymptotic methods
- geometry
- mathematical biology
- partial differential equations
- quantum field theory
- singularity theory
- stochastic analysis
- standard model/string theory.

By completing the first semester you qualify for the PG certificate. By completing the second, you qualify for the PG Diploma. Then, by completing your dissertation, you qualify for the MSc.

Key Facts

REF 2014
92% of our research impact judged at outstanding and very considerable, 28% improvement in overall research at 4* and 3*.

Facilities
A dedicated student resource suite is available in the Department, with computer and reading rooms and a social area.

Why Department of Mathematical Sciences?

Range and depth of study options

We offer a very wide range of modules, from advanced algebra and geometry, to partial differential equations, probability theory, stochastic analysis, and mathematical physics. With these you can tailor your programme to specialise in one of these areas, or gain a broad understanding of several. This allows you to build up the required background for the project and dissertation modules, which offer the opportunity to undertake an in-depth study of a topic of your choice, supervised by a leading expert in the field.

Exceptional employability

At Liverpool, we listen to employers’ needs. Alongside key problem solving skills, employers require strong communication skills. These are integral to this programme. Graduates go on to research degrees, or become business and finance professionals, or to work in management training, information technology, further education or training (including teacher training) and scientific research and development.

Teaching quality

We are proud of our record on teaching quality, with five members of the Department having received the prestigious Sir Alastair Pilkington Award for Teaching. We care about each student and you will find the staff friendly and approachable.

Accessibility

We take students from a wide variety of educational backgrounds and we work hard to give everyone the opportunity to shine.

Supportive atmosphere

We provide high quality supervision and teaching, computer labs, and and you will benefit from the friendly and supportive atmosphere in the Department, as evidenced by student feedback available on our university website. A common room and kitchen for the exclusive use of the Department’s students, and a lively maths society help to foster a friendly and supportive environment.

Career prospects

The excellent University Careers Service is open to all postgraduates. Graduates of the MSc and PhD programmes move on to many different careers. Recent graduates have moved into fast track teacher programmes, jobs in finance (actuarial, banking, insurance), software development, drugs testing and defence work, as well as University postdoctoral or lecturing posts. The MSc programme is of course a natural route into doctoral study in Mathematics and related fields, both at Liverpool and elsewhere. Some of our PhD students move on to postdoctoral positions and to academic teaching jobs and jobs in research institutes, both in the UK and elsewhere.

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Mathematical finance is an area of applied mathematics where concepts and techniques that lie close to the heart of pure mathematics are applied routinely to solve a great variety of important practical problems arising in the day-to-day business of the world's financial institutions. Read more

About the course

Mathematical finance is an area of applied mathematics where concepts and techniques that lie close to the heart of pure mathematics are applied routinely to solve a great variety of important practical problems arising in the day-to-day business of the world's financial institutions.

The objective of the Brunel MSc in Financial Mathematics is to guide students through to a mastery of the sophisticated mathematical ideas underlying modern finance theory, along with the associated market structures and conventions, with emphasis on:

- The modelling of the dynamics of financial assets, both in equity markets and in fixed-income markets
- The pricing and hedging of options and other derivatives, and
- The quantification and management of financial risk.

Candidates are also provided with the means to master the numerical and computational skills necessary for the practical implementation of financial models, thus enabling you to put theory into practice and putting you in a good position to carry out work for a financial institution. We therefore offer a programme that provides a balanced mixture of advanced mathematics (including modern probability theory and stochastic calculus), modern finance theory (including models for derivatives, interest rates, foreign exchange, equities, commodities, and credit), and computational technique (GPU-based high-performance computing).

The MSc in Financial Mathematics offers a range of exciting modules during the Autumn and the Spring terms, followed by an individual research project leading to a dissertation that is completed during the Summer term.

Aims

Financial mathematics is a challenging subject, the methods of which are deployed by sophisticated practitioners in financial markets on a daily basis. It builds on the application of advanced concepts in modern probability theory to enable market professionals to tackle and systematically resolve a huge range of issues in the areas of pricing, hedging, risk management, and market regulation. The main objective of the Brunel MSc in Financial Mathematics is to provide candidates with the knowledge they need to be able to enter into this exciting new area of applied mathematics and to position themselves for the opportunity to work in financial markets.

Among the main distinguishing features of our programme are the following:

We aim to teach the key ideas in financial asset pricing theory from a thoroughly modern perspective, using concepts and methods such as pricing kernels, market information filtrations, and martingale techniques, as opposed say to the more traditional but old-fashioned approach based on the historical development of the subject.

In our programme candidates are asked at each stage to undertake a critical re-examination of the hypotheses implicit in any financial model, with a view to gaining a clear grasp of both its strengths and its limitations.

The programme includes courses on high-performance computing that provide candidates with the techniques whereby financial models can be implemented.

Course Content

Programme structure

The programme offers five "compulsory" modules, taken by all candidates, along with a variety of elective modules from which students can pick and choose. There are lectures, examinations and coursework in eight modules altogether, including the five compulsory modules. Additionally, all students complete an individual research project on a selected topic in financial mathematics, leading to the submission of a dissertation.

Compulsory modules:

Probability and stochastics
Financial markets
Option pricing theory
Interest rate theory
Financial computing I

Elective Modules:

Portfolio theory
Information in finance with application to credit risk management
Mathematical theory of dynamic asset pricing
Financial computing II
Statistics for Finance
Financial Mathematics Dissertation

Special Features

The Department of Mathematics, home to its acclaimed research centre CARISMA, has a long tradition of research and software development, in collaboration with various industry partners, in the general area of risk management.

The Department is a member of the London Graduate School in Mathematical Finance, which is a consortium of mathematical finance groups of Birkbeck College, Brunel University London, Imperial College London, King’s College London, London School of Economics, and University College London. There is a strong interaction between the financial mathematics groups of these institutions in the greater London area, from which graduates can benefit. In particular there are a number of research seminars that take place regularly throughout the year which students are welcome to attend.

Assessment

Assessment is by a combination of coursework, examination, and dissertation. Examinations are held in May. The MSc degree is awarded if the student reaches the necessary overall standard on the taught part of the course and submits a dissertation that is judged to be of the required standard. Specifically, to qualify for the MSc degree, the student must: (a) take examinations in eight modules including the four compulsory modules, (b) attain the minimum grade profile (or better) required for a Masters degree and (c) submit a dissertation of the required standard. If a student does not achieve the requirements for the degree of MSc, they may, if eligible, be awarded a Postgraduate Diploma.

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This unique Masters in Applied Statistics in Health Sciences provides an opening to a career as an applied statistician, without having previously studied statistics. Read more
This unique Masters in Applied Statistics in Health Sciences provides an opening to a career as an applied statistician, without having previously studied statistics.

The course is run in collaboration with the Animal and Plant Health Agency (APHA), an Executive Agency of the Department for Environment, Food & Rural Affairs (Defra). Statisticians from APHA, as well as those who have extensive experience in working with the National Health Service in Scotland, will provide lectures based around real-life problems and data from the health sciences.

Although the programme is focused on health, the skill set provided will also equip you with the necessary training to work as an applied statistician in other areas such as insurance, finance and commerce.

What you'll learn

The three compulsory modules covered in Semester 1 will equip you with fundamental probability and data analysis skills. In Semester 2 there's four compulsory modules, each focusing on a different applied element of being a statistician. The course concludes with a research project which will involve the analysis of a real-life data set.

Programme skills set
On the programme you'll acquire:
-in-depth knowledge of modern statistical methods that are used to analyse and visualise real-life data sets and the experience of how to apply these methods in a professional setting
-skills in using statistical software packages that are used in government, industry and commerce
-the ability to interpret the output from statistical tests and data analyses and communicate your findings to a variety of audiences including health professionals, scientists, government officials, managers and stakeholders who may have an interest in the problem
-problem solving and high numeracy skills that are widely sought after in the commercial sector
-practical experience of statistical consultancy and how to interact with professionals who require statistical analyses of their data
-through the contacts with APHA and NHS staff, an understanding of what it's like to work as an applied statistician in practice including, for example, during disease outbreaks

Guest lectures
Several modules will be taught by academics who also work for other organisations including government and health services.

Facilities

The Department of Mathematics & Statistics has teaching rooms which provide you with access to modern teaching equipment and computing laboratories that are state-of-the-art with all necessary software available. You'll also have a common room facility, a modern and flexible area which is used for individual and group study work, and also a relaxing social space.

The Department of Mathematics & Statistics

At the heart of the Department of Mathematics & Statistics is the University’s aim of developing useful learning. We're an applied department with many links to industry and government. Most of the academic staff teaching on this course hold joint-appointments with, or are funded by, other organisations, including APHA, Public Health and Intelligence (Health Protection Scotland), Greater Glasgow and Clyde Health Board and the Marine Alliance for Science and Technology Scotland (MASTS). We bridge the gap between academia and real-life. Our research has societal impact.

Course content

Semester 1 Compulsory classes:
The three compulsory classes covered in semester 1 will equip you with fundamental probability and data analysis skills.

-Foundations of Probability & Statistics
-Data Analytics in R
-Applied Statistical Modelling

Semester 2 Compulsory classes:
Each class focuses on a different applied element of being a statistician.

-Medical Statistics
-Bayesian Spatial Statistics
-Effective Statistical Consultancy
-Risk Analysis
-Survey Design & Analysis
-Semester 3

Learning & teaching

Classes are delivered by a number of teaching methods:
-lectures (using a variety of media including electronic presentations and computer demonstrations)
-tutorials
-computer laboratories
-coursework
-projects

Teaching is student-focused, with students encouraged to take responsibility for their own learning and development. Classes are supported by web-based materials.

Assessment

The form of assessment varies for each class. For most classes the assessment involves both coursework and examinations.

How can I fund my course?

A number of scholarships are available for outstanding UK, EU and international applicants. For details, please visit our scholarship search: https://www.strath.ac.uk/studywithus/scholarships/

Scottish students:
Students living in Scotland can find out more about funding from the Student Awards Agency Scotland.

English/EU students:
Students ordinarily resident in England may be eligible to apply for a loan of up to £10,000 to cover their tuition fees and living costs. Students resident in the EU may also apply.

Careers

There are many exciting career opportunities for graduates in applied statistics. The practical, real-life skills that you'll gain means you'll be much in demand in international organisations. A report by the Association of the British Pharmaceutical Industry identified statistics and data mining as “two key areas in which a 'skills gap' is threatening the UK's biopharmaceutical industry.”

Typical employers of statisticians and data analysts include:

-Government
-Health services
-Pharmaceutical companies
-Human, animal, plant and environmental research institutes
-Insurance companies
-Banks
-Internet information providers such as Google
-Retailers

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The techniques we use to model and manipulate data guide the political, financial and social decisions that shape our modern society and are the basis of growth of the economy and success of businesses. Read more
The techniques we use to model and manipulate data guide the political, financial and social decisions that shape our modern society and are the basis of growth of the economy and success of businesses. Technology is growing and evolving at an incredible speed, and both the rate of growth of data we generate and the devices we use to process it can only increase.

Data science is a growing and important field of study with a fast-growing number of jobs and opportunities within the private and public sector. The application of theory and methods to real-world problems and applications is at the core of data science, which aims especially to use and to exploit big data.

If you are interested in solving real-world problems, you like to develop skills to use smart devices efficiently, you want to use and to foster your understanding of mathematics, and you are interested and keen to use statistical techniques and methods to interpret data, MSc Data Science at Essex is for you. You study a balance of solid theory and practical application including:
-Computer science
-Programming
-Statistics
-Data analysis
-Probability

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

You also benefit from being taught in our School of Computer Science and Electronic Engineering, who are ranked Top 10 in the UK in the 2015 Academic Ranking of World Universities, with more than two-thirds of their research rated ‘world-leading’ or ‘internationally excellent’ (REF 2014).

The collaborative work between our departments has resulted in well-known research in areas including artificial intelligence, data analysis, data analytics, data mining, data science, machine learning and operations research.

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.

The academic staff in our School of Computer Science and Electronic Engineering are conducting world-leading research in areas such as evolutionary computation, brain-computer interfacing, intelligent inhabited environments and financial forecasting.

Specialist staff working on data analytics include Dr Paul Scott, who researches data mining, models of memory and attention, and artificial intelligence, and Professor Maria Fasli, who researches data exploration, analysis and modelling of complex, structured and unstructured data, big data, cognitive agents, and web search assistants.

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 have six laboratories that are exclusively for computer science and electronic engineering students
-All computers run either Windows 7 or are dual boot with Linux
-Software includes Java, Prolog, C++, Perl, Mysql, Matlab, DB2, Microsoft Office, Visual Studio, and Project
-You have access to CAD tools and simulators for chip design (Xilinx) and computer networks (OPNET)
-We also have specialist facilities for research into areas including non-invasive brain-computer interfaces, intelligent environments, robotics, optoelectronics, video, RF and MW, printed circuit milling, and semiconductors
-We host regular events and seminars throughout the year
-Collaborate with the Essex Institute of Data Analytics and Data Science (IADS) and the ESRC Business and Local Government (BLoG) Data Research Centre of the University of Essex
-The UK Data Archive and the Institute for Social and Economic Research (ISER) at Essex contribute to our internationally outstanding data science environment

Your future

With a predicted shortage of data scientists, now is the time to future-proof your career. Data scientists are required in every sector, carrying out statistical analysis or mining data on social media, so our course opens the door to almost any industry, from health, to government, to publishing.

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.

Example structure

-Dissertation (optional)
-MSc Project and Dissertation (optional)
-Applied Statistics
-Machine Learning and Data Mining
-Modelling Experimental Data
-Text Analytics
-Artificial Neural Networks (optional)
-Bayesian Computational Statistics (optional)
-Big-Data for Computational Finance (optional)
-Combinatorial Optimisation (optional)
-High Performance Computing (optional)
-Natural Language Engineering (optional)
-Nonlinear Programming (optional)
-Professional Practice and Research Methodology (optional)
-Programming in Python (optional)
-Information Retrieval (optional)
-Data Science and Decision Making (optional)
-Research Methods (optional)
-Statistical Methods (optional)
-Stochastic Processes (optional)

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Statistics is one of the most important fields of study in the world. The techniques we use to model and manipulate data guide the political, financial and social decisions that shape our modern society. Read more
Statistics is one of the most important fields of study in the world. The techniques we use to model and manipulate data guide the political, financial and social decisions that shape our modern society. If you are a logical person and enjoy solving problems, statistics at Essex is for you.

Our Department of Mathematical Sciences embraces pure mathematics, applied mathematics and statistics, and operational research, and our course offers you the opportunity to study statistics alongside other mathematical subjects.

Providing a balance of solid statistical theory and practical application, this course builds your knowledge in all areas of statistics, data analysis and probability. You also have the opportunity to specialise, taking optional modules in topics including:
-Survey methodology
-Operations research
-Applied mathematics
-Computer science

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

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

Working in industries such as health, business, social care and finance, graduates are consistently in demand, working on projects such as efficacy of social policy, comparable data of cardiac rehabilitation and manipulation of raw data for academic research.

Our Masters graduates have progressed into careers in banking and finance, actuarial sciences, biological sciences, market research and statistics, management and consultancy etc.

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.

Example structure

-Modelling Experimental Data
-Statistical Methods
-Stochastic Processes
-Applied Statistics
-Bayesian Computational Statistics
-Research Methods
-Dissertation
-Nonlinear Programming (optional)
-Financial Modelling (optional)
-Research Methods in Finance: Empirical Methods in Finance (optional)
-Machine Learning and Data Mining (optional)
-Cloud Technologies and Systems (optional)
-Time Series Econometrics (optional)
-Panel Data Methods (optional)
-Topics in Contemporary Social Theory (optional)
-Introduction to Survey Design and Management (optional)
-Applied Sampling (optional)

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Actuaries provide assessments of financial security systems, with a focus on their complexity, their mathematics, and their mechanisms. Read more
Actuaries provide assessments of financial security systems, with a focus on their complexity, their mathematics, and their mechanisms. Actuaries quantify the probability and manage the risk of future events in areas such as insurance, healthcare, pensions, investment, and banking and also in non-financial areas. This course is taught by the Department of Mathematical Sciences and is intended for students with a first degree in mathematics, statistics, economics or finance who would like to acquire knowledge in actuarial science.

Our MSc Actuarial Science course is based on the syllabus of the majority of the Core Technical subjects of the Institute and Faculty of Actuaries, so you’ll cover Core Technical subjects as part of your course (CT2 or CT3, depending on the optional module selected, CT4, CT5, CT6, and CT8). This focus on up-to-date research findings in actuarial methodologies and actuarial applications means that you gain a solid training in actuarial modelling and actuarial analysis.

It is also possible to specialise on a topic of choice, with options including:
-Actuarial and Financial Modelling
-General Insurance
-Life Insurance

You will also have the chance to study a problem in depth through a Master's thesis project on a subject chosen by you or your supervisor.

As part of our Department of Mathematical Sciences you’re a member of an inclusive and approachable research community with an international reputation in many areas including semi-group theory, optimisation, probability, applied statistics, bioinformatics and mathematical biology.

Our expert staff

As well as being world-class academics, many of our academics have won research awards and grants from some of the largest actuarial society’s worldwide, national or regional awards for lecturing, and many of them are qualified and accredited teachers.

Teaching on our course are expert academics and practising actuaries. The key departmental contacts for our MSc Actuarial Science are Keith Bannister, Dr Haslifah Hashim, and Dr Spyridon Vrontos.
-Keith Bannister is a qualified actuary, and a Fellow of the Institute of Actuaries and Faculty of Actuaries; he lectures part-time in Actuarial Science.
-Dr Hashim specialises in life and general insurance, pensions, financial mathematics, enterprise risk management, forensic economics, and Islamic finance and takaful.
-Dr Vrontos specialises in actuarial mathematics and modelling, asset-liability management and performance measurement for pension funds, hedge funds and mutual funds, risk management and solvency, and risk theory.

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

Your future

As a new course, we expect our graduates of MSc Actuarial Science to become actuaries in a range of industries. It is predicted by the US Department of Labor that the employment of actuaries is expected to grow faster than any other occupation, making it a great prospect for a graduate job.

Aside from a rewarding career as an actuary (actuaries are in the top ten jobs for 2016, careercast.com), clear thinkers are required in every profession, so the successful mathematician has an extensive choice of potential careers. The Council for Mathematical Sciences offers further information on careers in mathematics.

We also work with the university’s Employability and Careers Centre to help you find out about further work experience, internships, placements, and voluntary opportunities.

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 department is strongly committed to research and to the promotion of graduate activities.

Example structure

Postgraduate study is the chance to take your education to the next level. The combination of compulsory and optional modules means our courses help you develop extensive knowledge in your chosen discipline, whilst providing plenty of freedom to pursue your own interests. Our research-led teaching is continually evolving to address the latest challenges and breakthroughs in the field, therefore to ensure your course is as relevant and up-to-date as possible your core module structure may be subject to change.

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

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

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

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

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

Academic excellence

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

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

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

Course content

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

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

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

Course structure

Compulsory modules

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

Optional modules

You'll also take two optional modules.

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

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

Learning and teaching

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

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

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

Assessment

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

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

Career opportunities

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

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

Careers support

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

Read more about our careers and professional development support.

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



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About the MSc programme. The MSc Statistics provides intensive training in statistics applicable to the social sciences, economics and finance. Read more

About the MSc programme

The MSc Statistics provides intensive training in statistics applicable to the social sciences, economics and finance.

The aim of the programme is to foster an interest in theoretical and applied statistics and equip you for work as a professional statistician. You will learn to analyse and critically interpret data, build statistical models of real situations, and use programming tools and statistical software packages. 

The compulsory course will provide you with comprehensive coverage of fundamental aspects of probability and statistical methods and principles. It provides the foundations for the optional courses on more advanced statistical modelling, computational methods, statistical computing and advanced probability theory. Options also include specialist courses from the Departments of Methodology, Management, Mathematics, Economics and Social Policy. 

Graduates of the programme are awarded Graduate Statistician (GradStat) status by the Royal Statistical Society. 

MSc Statistics (Research)

The research stream is similar to the MSc Statistics nine-month programme but involves a compulsory dissertation which replaces one unit's worth of optional courses and extends the length of the programme to 12 months. 

Graduates of the programme are awarded Graduate Statistician (GradStat) status by the Royal Statistical Society.

Graduate destinations

Students on this programme have excellent career prospects. Former students have taken up positions in consulting firms, banks and in the public sector. Many go on to take higher degrees. Graduates of the MSc are awarded Graduate Statistician (GradStat) status by the Royal Statistical Society.

Further information on graduate destinations for this programme



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Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Stochastic Processes. Read more

Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Stochastic Processes: Theory and Application at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017).

The MRes in Stochastic Processes: Theory and Application is delivered through optional modules for the taught element followed by a large research project that contributes to the field in an explicit way, rather than merely applying existing knowledge.

The Department of Mathematics hosts one of the strongest research groups in probability theory, especially in stochastic processes, in the UK. The senior members of this group are world leaders in their fields.

The Department’s research groups include:

Algebra and Topology Group

Areas of interest include: Noncommutative geometry, Categorical methods in algebra and topology, Homotopy theory and homological algebra and others.

Analysis and Nonlinear Partial Differential Equations Group

Areas of interest include: Reaction-diffusion and reaction-diffusion-convection equations and systems, Navier–Stokes equations in fluid dynamic, Complexity in the calculus of variations and others.

Stochastic Analysis Group

Areas of interest include: Functional inequalities and applications, Lévy-type processes, Stochastic modelling of fractal, multi-fractal and multi-scale systems, Infinite dimensional stochastic analysis and others.

Mathematical Methods in Biology and Life Sciences Group

Areas of interest include: Mathematical pharmacology; heat and mass transfer models for plant cooling; modelling cellular signal transduction dynamics; mathematical oncology: multi-scale modelling of cancer growth, progression and therapies, and modelling-optimized delivery of multi-modality therapies; multi-scale analysis of individual-based models; spreading speeds and travelling waves in ecology; high performance computing.

Key Features

The Department of Mathematics hosts one of the strongest research groups in probability theory, especially in stochastic processes, in the UK. The senior members of this group are world leaders in their fields.

Course Content

As a student on the MRes Stochastic Processes programme you will study a range of topics for the taught element including:

Stochastic Calculus based on Brownian Motion

Levy processes and more general jump processes

The advanced Black-Scholes theory

Theory and numerics of parabolic differential equations

Java programming

The Stochastic Processes: Theory and Application course consists of a taught part (60 credits) and a research project (120 credits). Students will have a personal supervisor for their research project from the start of their studies.

Research projects could be of a theoretical mathematical nature, or they could be more applied, for example in financial mathematics or actuarial studies. Some of the research projects will be of an interdisciplinary character in collaboration with some of Swansea's world class engineers. For such projects it is likely that EPSRC funding would be available.

Facilities

The Aubrey Truman Reading Room, located in the centre of the Department of Mathematics, houses the departmental library and computers for student use. It is a popular venue for students to work independently on the regular example sheets set by their lecturers, and to discuss Mathematics together.

Our main university library, Information Services and Systems (ISS), contains a notably extensive collection of Mathematics books.

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, statistical 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.



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This Masters in Biostatistics will provide you with knowledge and experience of the principles, theory and practical skills of statistics; previous study of statistics is not required. Read more

This Masters in Biostatistics will provide you with knowledge and experience of the principles, theory and practical skills of statistics; previous study of statistics is not required.

Why this programme

  • The Statistics Group at Glasgow is a large group, internationally renowned for its research excellence.
  • Our Statistics MSc programmes benefit from close links lecturers have with industry and non-governmental organisations such as NHS and SEPA.
  • Our expertise spans topics including: biostatistics and statistical genetics; environmental statistics; statistical methodology; statistical modelling and the scholarship of learning and teaching in statistics.
  • You will develop a thorough grasp of statistical methodology, before going on to apply statistical skills to solve real-life problems.
  • You will be equipped with the skills needed to begin a career as a professional statistician; previous study of statistics is not required.

Programme structure

Modes of delivery of the Masters across the Statistics programmes include lectures, laboratory classes, seminars and tutorials and allow students the opportunity to take part in lab, project and team work.

Core courses (compulsory)

  • Bayesian statistics
  • Biostatistics 
  • Generalised linear models 
  • Introduction to R programming 
  • Probability 1
  • Regression models 
  • Statistical inference 1
  • Statistics project and dissertation.

Optional courses (five chosen, but at least one course must be from Group 1)

Group 1

  • Data analysis 
  • Professional skills.

Group 2

  • Data management and analytics using SAS
  • Design of experiments 
  • Functional data analysis 
  • Spatial statistics 
  • Statistical genetics 
  • Time series.

1 Any student who, in the course of study for his or her first degree, has already completed the equivalent of the Probability and/or Statistical inference courses can substitute these courses by any other optional course (including optional courses offered as part of the MRes in Advanced Statistics). The choice of substituting courses is subject to approval by the Programme Director.

Summer (May – August)

Statistics project and dissertation (60) - applying statistical methods and modelling to data collected from research in a biomedical discipline, assessed by a dissertation.

Career prospects

Our graduates have an excellent track record of gaining employment in many sectors including medical research, the pharmaceutical industry, finance and government statistical services, while others have continued to a PhD.



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This Masters in Environmental Statistics will provide you with knowledge and experience of the principles, theory and practical skills of statistics; previous study of statistics is not required. Read more

This Masters in Environmental Statistics will provide you with knowledge and experience of the principles, theory and practical skills of statistics; previous study of statistics is not required.

Why this programme

  • The Statistics Group at Glasgow is a large group, internationally renowned for its research excellence.
  • Our Statistics MSc programmes benefit from close links lecturers have with industry and non-governmental organisations such as NHS and SEPA.
  • Our expertise spans topics including: biostatistics and statistical genetics; environmental statistics; statistical methodology; statistical modelling and the scholarship of learning and teaching in statistics.
  • You will develop a thorough grasp of statistical methodology, before going on to apply statistical skills to solve real-life problems.
  • You will be equipped with the skills needed to begin a career as a professional statistician; previous study of statistics is not required.
  • You will be taught by world-leading experts in their fields and will participate in an extensive and varied seminar programme, are taught by internationally renowned lecturers and experience a wide variety of projects.
  • Our students graduate with a varied skill set, including core professional skills, and a portfolio of substantive applied and practical work.

Programme structure

Modes of delivery of the Masters across the Statistics programmes include lectures, laboratory classes, seminars and tutorials and allow students the opportunity to take part in lab, project and team work.

Core courses (compulsory)

  • Bayesian statistics 
  • Data analysis 
  • Environmental statistics 
  • Generalised linear models 
  • Introduction to R programming
  • Principles of GIS (10)
  • Probability 1
  • Regression models 
  • Spatial statistics 
  • Statistical inference 1
  • Time series 
  • Topographic mapping and landscape monitoring
  • Statistics project and dissertation.

1 Any student who, in the course of study for his or her first degree, has already completed the equivalent of the Probability and/or Statistical inference courses can substitute these courses by any other optional course (including optional courses offered as part of the MRes in Advanced Statistics). The choice of substituting course is subject to approval by the Programme Director.

Summer (May – August)

Statistics project and dissertation (60) - applying statistical methods and modelling to data collected from research in environmental science, assessed by a dissertation.

Career prospects

Our graduates have an excellent track record of gaining employment in many sectors including medical research, the pharmaceutical industry, finance and government statistical services, while others have continued to a PhD.

Graduates of this programme have gone on to positions such as:

Research Officer Medical Statistics at Kenya Medical Research Institute (KEMRI) Welcome Trust.



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This Masters in Statistics will provide you with knowledge and experience of the principles, theory and practical skills of statistics. Read more

This Masters in Statistics will provide you with knowledge and experience of the principles, theory and practical skills of statistics.

Why this programme

  • The Statistics Group at Glasgow is a large group, internationally renowned for its research excellence.
  • Our expertise spans topics including: biostatistics and statistical genetics; environmental statistics; statistical methodology; statistical modelling and the scholarship of learning and teaching in statistics.
  • Our Statistics MSc programmes benefit from close links lecturers have with industry and non-governmental organisations such as NHS and SEPA.
  • You will develop a thorough grasp of statistical methodology, before going on to apply statistical skills to solve real-life problems.
  • You will be equipped with the skills needed to begin a career as a professional statistician; previous study of statistics is not required.
  • You will be taught by world-leading experts in their fields and will participate in an extensive and varied seminar programme, are taught by internationally renowned lecturers and experience a wide variety of projects.
  • Our students graduate with a varied skill set, including core professional skills, and a portfolio of substantive applied and practical work.

Programme structure

Modes of delivery of the Masters across the Statistics programmes include lectures, laboratory classes, seminars and tutorials and allow students the opportunity to take part in lab, project and team work.

Core courses (compulsory)

  • Bayesian statistics
  • Generalised linear models 
  • Introduction to R programming 
  • Probability 1
  • Regression models 
  • Statistical inference 1
  • Statistics project and dissertation.

Optional courses (six chosen, but at least one course must be from Group 1)

Group 1

  • Data analysis 
  • Professional skills.

Group 2

  • Biostatistics 
  • Computational inference 
  • Data management and analytics using SAS 
  • Design of experiments 
  • Environmental statistics 
  • Financial statistics 
  • Functional data analysis 
  • Machine learning
  • Multivariate methods 
  • Spatial statistics 
  • Statistical genetics 
  • Stochastic processes 
  • Time series.

1 Any student who, in the course of study for his or her first degree, has already completed the equivalent of the Probability and/or Statistical inference courses can substitute these courses by any other optional course (including optional courses offered as part of the MRes in Advanced Statistics). The choice of substituting courses is subject to approval by the Programme Director.

Summer (May – August)

Statistics project and dissertation (60) - assessed by a dissertation.

Career prospects

Our graduates have an excellent track record of gaining employment in many sectors including finance, medical research, the pharmaceutical industry and government statistical services, while others have continued to a PhD.



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