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We will provide you with an advanced and challenging study of the main management disciplines of finance, marketing, supply chain and human resources. Read more
We will provide you with an advanced and challenging study of the main management disciplines of finance, marketing, supply chain and human resources. You will apply modern business and management techniques to an organisation's problems in the context of the wider business world and global community.

This is your opportunity to improve your personal and interpersonal competencies, intellectual skills and self-motivation through problem-solving, mutual support, participative personal development planning and reflective learning.

This course provides an opportunity for graduates with a non-business degree background to gain knowledge of management principles and practice. It is also recommended if you are a graduate with a businessor management degree seeking to achieve a management-based masters.

Faculty of Business & Law website - hhttps://www.leedsmet.ac.uk/fbl/

January entrants please note: in order to complete 12 months of academic study delivered in University term time, the total length of your programme will be 18 months to include recognised University vacation periods.

- Research Excellence Framework 2014: twice as many of our staff - 220 - were entered into the research assessment for 2014 compared to the number entered in 2008

Visit the website http://courses.leedsbeckett.ac.uk/management_msc

Mature Applicants

Our University welcomes applications from mature applicants who demonstrate academic potential. We usually require some evidence of recent academic study, for example completion of an access course, however recent relevant work experience may also be considered. Please note that for some of our professional courses all applicants will need to meet the specified entry criteria and in these cases work experience cannot be considered in lieu.

If you wish to apply through this route you should refer to our University Recognition of Prior Learning policy that is available on our website (http://www.leedsbeckett.ac.uk/studenthub/recognition-of-prior-learning.htm).

Please note that all applicants to our University are required to meet our standard English language requirement of GCSE grade C or equivalent, variations to this will be listed on the individual course entry requirements.

Careers

Successful achievement of our MSc Management will enable you to apply for a general management role within a range of different businesses both in the public and private sector. The starting salaries will vary depending on your previous experience, but this qualification will add value to you by equipping you with the management skills to complement your previous area of study.

- Business Development Manager
- General Manager
- Project Manager
- Area Manager

Careers advice: The dedicated Jobs and Careers team offers expert advice and a host of resources to help you choose and gain employment. Whether you're in your first or final year, you can speak to members of staff from our Careers Office who can offer you advice from writing a CV to searching for jobs.

Visit the careers site - https://www.leedsbeckett.ac.uk/employability/jobs-careers-support.htm

Careers

If you wish to develop your career in general management, this course can help you develop the skills you'll need to progress in management. You will acquire the confidence and competence to address the demands placed upon managers, providing you with a recognised qualification and a platform to progress in your chosen field. As the course is open to both non-business and business graduates, there is a mix of skills and experience on the course which enables participants to enhance one another's learning experiences.

The teaching team consists of experienced deliverers of management education, both within higher education as well as for several professional bodies. They also possess many years of practical managerial experience, enabling them to relate theory to practice as well as bringing the latest industry issues and trends into the classroom.

At Leeds Business School we're dedicated to supporting your professional development - that's why we offer a guest lecture programme. Past speakers include the CEO of the London Stock Exchange, Shadow Chief Secretary to the Treasury, past Chair and President of the Academy of Marketing, Chief Executive of the British Bankers Association, the Chief Economist of Yorkshire Bank and the Editor of Cosmopolitan. To see our full programme and to register for a lecture click here (http://www.leedsmet.ac.uk/guestspeakers).

Core Modules

Business Data: Management & Analysis
Develop competences in data collection issues and decision analysis techniques. You will also gain an understanding of the use of linear programming in optimisation problems and the role of statistical inference in model building.

Corporate Strategy
Develop a strategic organisational perspective as well as a basis for progression and application of strategic level skills, competencies, and decision-making capability.

Global Supply Chain Management
You'll be introduced to the supply chain concept by observing a variety of companies and how they are changing their business practices to achieve corporate objectives in the current economic climate.

Management, People & Organisations
Develop functional knowledge and a critical understanding of key perspectives on human behaviour within an organisation and on the nature and processes of organising and managing human activity.

Managing Financial Resources
Gain a critical understanding of contemporary accounting and financing principles which support business decision-making and financial resourcing in both the private and public sectors.

Marketing
Develop your knowledge and understanding of the principles and theoretical foundations which govern the modern marketing environment, allowing you to progress in a specialised area of marketing such as international or services marketing.

Dissertation
You will carry out an in-depth research project in a subject area that is appropriate to the course and of particular interest to you.

Garry Carr

Senior Lecturer

"Teaching on the MSc Management course is an exciting prospect, as our students arrive from a variety of backgrounds, each with varying experiences, and this really enriches the classroom experience."

Garry has more than 20 years' experience teaching at both undergraduate and postgraduate level. He is a Senior Fellow of the Higher Education Academy and a member of the American Academy of Management. He has consultancy experience within the private and public sectors and has research interests in strategic management, the creative industries and organisational theory.

Facilities

- Library
Our libraries are two of the only university libraries in the UK open 24/7 every day of the year. However you like to study, the libraries have got you covered with group study, silent study, extensive e-learning resources and PC suites.

- The Rose Bowl
The Rose Bowl has impressive teaching spaces, auditoriums, conference facilities and an outstanding local reputation as a business hub. The Rose Bowl puts our students at the centre of a dynamic business community.

Find out how to apply here - http://www.leedsbeckett.ac.uk/postgraduate/how-to-apply/

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Designed for aspiring finance professionals who want to gain specialist knowledge, this course will equip you with the skills required for seeking employment in the increasingly complex and demanding financial services sector. Read more
Designed for aspiring finance professionals who want to gain specialist knowledge, this course will equip you with the skills required for seeking employment in the increasingly complex and demanding financial services sector.

You will explore the theories and current practice in the finance industry from both a national and international perspective. The course blends theory with practice to provide you with the applied vocational skills that potential employers require.

You'll study in the heart of Leeds, which is the largest hub of financial services in the UK outside London. Leeds is home to many leading financial organisations and large professional services firms. You'll be taught by a range of highly experienced tutors with industrial, professional and academic knowledge.

We include a strong international dimension in the course content and attract students from as far and wide as China, India, Pakistan and Vietnam.

Faculty of Business & Law website (https://www.leedsmet.ac.uk/fbl/)
Request a call back (http://www.leedsmet.ac.uk/study/postgraduate.htm)

January entrants please note: in order to complete 12 months of academic study delivered in University term time, the total length of your programme will be 18 months to include recognised University vacation periods.

- Research Excellence Framework 2014: twice as many of our staff - 220 - were entered into the research assessment for 2014 compared to the number entered in 2008.

Visit the website http://courses.leedsbeckett.ac.uk/finance_msc

Mature Applicants

Our University welcomes applications from mature applicants who demonstrate academic potential. We usually require some evidence of recent academic study, for example completion of an access course, however recent relevant work experience may also be considered. Please note that for some of our professional courses all applicants will need to meet the specified entry criteria and in these cases work experience cannot be considered in lieu.

If you wish to apply through this route you should refer to our University Recognition of Prior Learning policy that is available on our website (http://www.leedsbeckett.ac.uk/studenthub/recognition-of-prior-learning.htm).

Please note that all applicants to our University are required to meet our standard English language requirement of GCSE grade C or equivalent, variations to this will be listed on the individual course entry requirements.

Careers

This course has a proven track record of graduates gaining employment in the financial services sector, such as banking or insurance. Others have entered into their family business, taking on a variety of management level roles. A small number have remained in the education sector to study a PhD and have entered into the teaching profession.

- Financial Analyst
- Financial Advisor
- Director of Finance
- Chief Financial Officer

Careers advice:
The dedicated Jobs and Careers team offers expert advice and a host of resources to help you choose and gain employment. Whether you're in your first or final year, you can speak to members of staff from our Careers Office who can offer you advice from writing a CV to searching for jobs.

Visit our careers site - https://www.leedsbeckett.ac.uk/employability/jobs-careers-support.htm

Course Benefits

Our MSc Finance is delivered in the heart of Leeds, which is the largest hub of financial services in the UK outside London and which is home to many leading financial organisations and large professional services firms.

The course is delivered by a range of highly experienced tutors with industrial, professional and academic experience. The course emphasises blending theory with practice and thus provides students with the applied vocational skills that potential employers require. It is international both in terms of content and the student mix which provides a multicultural learning environment.

At Leeds Business School we're dedicated to supporting your professional development - that's why we offer a guest lecture programme. Past speakers include the CEO of the London Stock Exchange, Shadow Chief Secretary to the Treasury, past Chair and President of the Academy of Marketing, Chief Executive of the British Bankers Association, the Chief Economist of Yorkshire Bank and the Editor of Cosmopolitan. To see our full programme and to register for a lecture click here (http://www.leedsmet.ac.uk/guestspeakers).

Core Modules

Corporate Finance
Evaluate the fundamental concepts and theories of modern finance, identifying how these can be effectively applied in both national and multinational organisations.

Financial Decision Analysis
Cover topics on decision theory (decision trees and tables), linear programming, regression, time series, portfolio optimisation, discounted cash flow and finance.

Financial Economics
Gain a comprehensive economic analysis of the operation, efficiency and dependencies between financial markets and their associated institutions. You will also assess the impact upon the world economy of any failure of the financial sector.

Managing Financial Resources
Gain a critical understanding of contemporary accounting and financing principles which support business decision-making and financial resourcing in both the private and public sectors.

Understanding the Economy
Develop knowledge and a critical understanding of the workings of a major economy which is subject to a constantly changing global environment, de-regulated financial systems, modern mass communication and international monetary flows.

Dissertation
You will carry out an in-depth research project in a subject area that is appropriate to the course and of particular interest to you.

Option Modules

Forensic Accounting
Discover the need for and role of corporate governance in the business environment, the role of IT in forensic accounting and fraud detection and the types and incidences of fraud.

Investment Fund Management
You will identify, understand, evaluate and compare types of investment for the private investor, including tools, methods and strategies.

Management of International Finance
Gain a comprehensive understanding of the economics of the operation and organisation of national and international financial systems.

"We are proud of the success of our national and international graduates."
- Professor Christopher Prince
Dean and Pro Vice Chancellor of the Faculty of Business and Law

Facilities

- Library
Our libraries are two of the only university libraries in the UK open 24/7 every day of the year. However you like to study, the libraries have got you covered with group study, silent study, extensive e-learning resources and PC suites.

- The Rose Bowl
The Rose Bowl has impressive teaching spaces, auditoriums, conference facilities and an outstanding local reputation as a business hub. The Rose Bowl puts our students at the centre of a dynamic business community.

Find out how to apply here - http://www.leedsbeckett.ac.uk/postgraduate/how-to-apply/

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The MSc Civil Engineering programme is ideal if you would like to broaden and deepen your technical knowledge of specialised civil engineering areas and develop a wider perspective and understanding of the issues facing the civil engineering industries. Read more
The MSc Civil Engineering programme is ideal if you would like to broaden and deepen your technical knowledge of specialised civil engineering areas and develop a wider perspective and understanding of the issues facing the civil engineering industries. It provides a distinctive educational platform to encourage the development of articulate, numerate, literate, imaginative, versatile, confident and inquisitive postgraduates who are able to link the theoretical with the practical.

About the course

The course is designed for those who have already graduated with a civil engineering or engineering-related degree. Successful completion of the MSc is designed to provide the educational base for progression to Chartered Engineer (CEng) status.

You will obtain advanced analytical skills in your chosen subject areas. You will have the opportunity to learn to design steel and concrete framed structures using modern structural analysis software, use advanced theory for the design and implementation of geotechnical works, apply advanced hydraulic concepts and model hydraulic systems, learn about advanced materials technologies and use advanced techniques to model transport and other systems. You will develop skills in project management and can choose whether you want to learn about environmental management or construction law and sustainable procurement.

In structures, you will also learn to assess existing buildings and design adaptations and apply the stiffness matrix method to analyse two-dimensional structures. In geotechnical engineering you will design earthworks, and slope and retaining walls. In hydraulics you will study open channel and pipe flow and urban pollution management. In materials you will learn about special concretes and sustainability and materials repair and rehabilitation. In transport you will apply linear programming and queuing theory to practical problems.

For more information please visit http://www.bolton.ac.uk/postgrad

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Businesses, organisations, and individuals all strive to work as effectively as possible. Operational research uses advanced statistical and analytical methods to help improve the complex decision-making processes to deliver a product or service. Read more
Businesses, organisations, and individuals all strive to work as effectively as possible. Operational research uses advanced statistical and analytical methods to help improve the complex decision-making processes to deliver a product or service. Working in this field, you might be identifying future needs for a business, evaluating the time-life value of a customer, or carrying out computer simulations for airlines.

Our MSc Statistics and Operational Research will appeal if your first degree included mathematics as its major subject, and we expect you to have prior knowledge of statistics – for example significance testing or basic statistical distributions – and operational research such as linear programming.

You specialise in areas including:
-Continuous and discrete optimisation
-Time series econometrics
-Heuristic computation
-Experimental design
-Machine learning
-Linear models

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

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

This course can also be studied to a PGDip level - for more information, please view this web-page: http://www.essex.ac.uk/courses/details.aspx?mastercourse=PG00808&subgroup=2

Our expert staff

Our Department of Mathematical 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

Our MSc Statistics and Operational Research will equip you with employability skills like problem solving, analytical reasoning, data analysis, and mathematical modelling, as well as training you in independent work, presentation and writing skills.

Your exposure to current active research areas, such as decomposition algorithms on our module, Combinatorial Optimisation, prepares you for further study at doctoral level. Graduates of this course now hold key positions in government, business and academia.

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

-Nonlinear Programming
-Combinatorial Optimisation
-Modelling Experimental Data (optional)
-Statistical Methods (optional)
-Stochastic Processes (optional)
-Applied Statistics (optional)
-Bayesian Computational Statistics
-Research Methods
-Dissertation
-Ordinary Differential Equations (optional)
-Graph Theory (optional)
-Partial Differential Equations (optional)
-Portfolio Management (optional)
-Machine Learning and Data Mining (optional)
-Evolutionary Computation and Genetic Programming (optional)
-Time Series Econometrics (optional)
-Panel Data Methods (optional)
-Applications of Data Analysis (optional)
-Mathematical Research Techniques Using Matlab (optional)

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The College of Liberal Arts and Sciences is a thriving center of intellectual excellence that encompasses 14 academic departments and 80 degree programs. Read more
The College of Liberal Arts and Sciences is a thriving center of intellectual excellence that encompasses 14 academic departments and 80 degree programs. Its more than 2,500 students are engaged in a wide variety of challenging courses and hands-on learning experiences that extend across all areas of the humanities and sciences – from the great philosophers and classic literature to the world economy and environmental sustainability.

At the core of each department are faculty members who have garnered national acclaim for their best-selling books, ground-breaking research and creative endeavors. Together, students and their professors explore globally significant subjects and work towards the goal of improving every aspect of the way in which human beings live. To learn more about a specific area of study, click on the left-hand navigation bar for a full listing of academic departments.

The department

The Department of Mathematics provides numerous undergraduate and graduate level courses that will enable you to master the mathematical methods and sophisticated reasoning and problem-solving skills essential to a wide variety of fields. In addition, the department offers a program to become an actuary.

The bachelor’s and master’s degree programs are designed to provide flexibility while emphasizing mathematical reasoning and problem solving, preparing the student for graduate school or a career in mathematics in secondary school teaching, business, industry, government or academia. In addition, a degree in mathematics is regarded as excellent preparation for entrance to professional schools of law, medicine or business.

M.S. in Applied Mathematics

The Master of Science degree program in Applied Mathematics offers specializations in either Classical Mathematics or Computer Mathematics. Classical Mathematics focuses on the foundations of modern mathematical theory, covering linear algebra, numerical methods and complex analysis. Computer Mathematics combines the fields of mathematics and technology through courses such as logic and information, applications of analysis, linear programming and statistics.

The faculty members in the Department of Mathematics are experts in areas such as topological groups, probability theory, differential geometry, number theory, dynamical systems and computer graphics, real analysis, numerical analysis, abstract algebra, combinatorics and history of mathematics.

Many of our graduates have gone on to receive Ph.D.’s from prestigious institutions. LIU Post graduates also are qualified for rewarding positions in actuarial science, insurance, finance, engineering, manufacturing and education.

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The MSc in Data Science & Analytics, jointly offered by the Department of Computer Science and the Department of Statistics, provides an education in the key principles of this rapidly expanding area. Read more
The MSc in Data Science & Analytics, jointly offered by the Department of Computer Science and the Department of Statistics, provides an education in the key principles of this rapidly expanding area. The combination of sophisticated computing and statistics modules will develop skills in database management, programming, summarisation, modelling and interpretation of data. The programme provides graduates with an opportunity, through development of a research project, to investigate the more applied elements of the disciplines.

Visit the website: http://www.ucc.ie/en/ckr49/

Course Details

The MSc in Data Science and Analytics is a significant collaboration between the Departments of Computer Science and Statistics; designed to provide graduates with the skills and knowledge required to help companies and public bodies deal with ever increasing and complex data. The programme emphasises the application of Computer Science and Statistics methodologies helping transform data into useful information that can support decision making.

Format

A typical 5 credit module:
• 2 lecture hours per week
• 1–2 hours of practicals per week
• Outside these regular hours students are required to study independently by reading and by working in the laboratories and on exercises.

Structure

Students must attain 90 credits through a combination of:

- Core Modules (30 credits)
- Elective Modules (30 credits)
- Dissertation (30 credits)

Part 1 (60 credits)

- Core Modules (30 credits) -

CS6405 Data Mining (5 credits) - Dr. Marc Van Dongen
ST6030 Foundations of Statistical Data Analytics (10 credits)
ST6033 Generalised Linear Modelling Techniques (5 credits)

- Database Modules -

Students who have adequate database experience take:

CS6408 Database Technology (5 credits) - Mr. Humphrey Sorensen
CS6409 Information Storage and Retrieval (5 credits) - Mr. Humphrey Sorensen

- Students who have not studied databases take:

CS6503 Introduction to Relational Databases (5 credits)
CS6505 Database Design and Administration (5 credits)

Elective Modules (30 credits)

Students must take at least 10 credits of CS (Computer Science) modules and at least 10 credits of ST (Statistics) modules from those listed below:

CS6322 Optimisation (5 credits) - Dr. Steve Prestwich
CS6323 Analysis of Networks and Complex Systems (5 credits) - Prof. Gregory Provan
CS6509 Internet Computing for Data Science (5 credits)
ST6032 Stochastic Modelling Techniques (5 credits)
ST6034 Multivariate Methods for Data Analysis (10 credits)
ST6035 Operations Research (5 credits)
ST6036 Stochastic Decision Science (5 credits)

- Programming Modules -

Students who have adequate programming experience take:

CS6406 Large-Scale Application Development and Integration l (5 credits) - Professor Gregory Provan
CS4607 Large-Scale Application Development and Integration ll (5 credits) - Professor Gregory Provan

- Students who have not studied programming take:

CS6506 Programming in Python (5 credits)
CS6507 Programme in Python with Data Science and Applications (5 credits) - Dr. Kieran Herley

Part 2 (30 credits)

Students select one of the following modules:

CS6500 Dissertation in Data Analytics (30 credits)
ST6090 Dissertation in Data Analytics (30 credits)

Assessment

Full details and regulations governing Examinations for each programme will be contained in the Marks and Standards 2015 Book and for each module in the Book of Modules 2015/2016 - http://www.ucc.ie/modules/

Postgraduate Diploma in Data Science and Analytics

Students who pass each of the taught modules may opt to exit the programme and be conferred with a Postgraduate Diploma in Data Science and Analytics.

Careers

This programme aims to prepare students to manage, analyse and interpret large heterogeneous data sources. Graduates will design, compare and select appropriate data analytic techniques, using software tools for data storage/management and analysis, machine learning, as well as probabilistic and statistical methods. Such abilities are at the core of companies that constantly face the need to deal with large data sets.

Companies currently seeking graduates with data analytics skills include: firms specialising in analytics, financial services and consulting, or governmental agencies.

Companies actively recruiting Computer Science graduates in 2014-15 include:

Accenture, Aer Lingus, Amazon, Apple, Bank of America Merrill Lynch, Bank of Ireland, BT, Cisco, CiTi-Technology, Cloudreach, Dell, Digital Turbine Asia Pacific, EMC, Enterprise Ireland, Ericsson, First Derivatives, Guidewire, IBM, Intel, Open Text, Paddy Power, Pilz, PWC, SAP Galway Transverse Technologies, Trend Micro, Uniwink, Version 1 (Software).

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

Funding and Scholarships

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

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The objective of this programme of study is to prepare professionals able to deal with complex systems using sophisticated mathematical tools, yet with an engineering attitude. Read more

Mission and goals

The objective of this programme of study is to prepare professionals able to deal with complex systems using sophisticated mathematical tools, yet with an engineering attitude. It harmonises a solid scientific background with a command of advanced methodologies and technologies. The programme is characterised by a continuous synergy between Applied Mathematics and Engineering disciplines- The students may choose among three specialisations:
- Computational Science and Engineering
- Applied Statistics
- Quantitative Finance

See the website http://www.polinternational.polimi.it/educational-offer/laurea-magistrale-equivalent-to-master-of-science-programmes/mathematical-engineering/

Career opportunities

The professional opportunities offered by this course are rather ample and varied: engineering consultancy companies that deal with complex computational problems; manufacturing or civil engineering companies where analyses based on the use of advanced mathematical tools are needed; banks, insurance companies and financial institutions making use of quantitative finance for risk analysis or forecast; companies that require statistical interpretation and the processing of complex data, or the simulation of different scenarios; public and private research institutes and laboratories.

Eligible students

Students holding a Bachelor degree in Mathematical Engineering, or in a related area with a solid background in the core disciplines of the programme, i.e. Applied Mathematics, Computer Science, Applied Physics or other Engineering disciplines are eligible for application. In particular, eligible students' past studies must include courses in different areas of Engineering (among Informatics, Economics & Business Organization, Electrotechnics, Automation, Electronics, Applied Physics, Civil Engineering) for at least 25% of the overall courses, as well as courses in different areas of Mathematics (Mathematical Analysis, Linear Algebra, Geometry, Probability, Statistics, Numerical Analysis, Optimization) for at least 33% of the overall courses.
The following tracks are available:
1. Computational Science and Engineering
2. Applied Statistics
3. Quantitative Finance

Eligible students must clearly specify the track they are applying for in their motivation letter.

Presentation

See http://www.polinternational.polimi.it/uploads/media/Mathematical_Engineering.pdf
The Master of Science in Mathematical Engineering (MSME) aims to form an innovative and flexible professional profile, endowed with a wide spectrum of basic scientific notions and engineering principles, together with a deep knowledge of modern pure and applied mathematical techniques. MSME is characterized by a continuous synergy between Mathematics and Engineering methods, oriented to the modelling, analysis and solution of complex planning, control and management problems, and provides the students with the possibility to face problems from various scientific, financial and/or technological areas. The MSME graduates can find employment in Engineering companies specialized in handling complex computational problems, requiring a multidisciplinary knowledge; in companies manufacturing industrial goods for which design analysis based on the use of advanced mathematical procedures are required; in service societies, banks, insurance companies, finance or consultant agencies for the statistical interpretation and the simulation of complex situations related to the analysis of large number of data (e.g. management and optimization of services, data mining, information retrieval) or for handling financial products and risk management; in public and private institutions. The programme is taught in English.

Subjects

Three main tracks available:
1. Computational Science for Engineering
Real and functional analysis; algorithms and parallel programming; numerical and theoretical analysis for partial differential equations; fluid mechanics; computational fluid dynamics advanced programming techniques for scientific computing;

2. Statistics
Real and functional analysis; algorithms and parallel programming; stochastic dynamical models; applied statistics, model identification and data analysis; Bayesian statistics

3. Mathematical Finance
Real and functional analysis; algorithms and parallel programming; stochastic differential equations; mathematical finance; financial engineering; model identification and data analysis.

In the motivation letter the student must clearly specify the track he/she is applying for.

See the website http://www.polinternational.polimi.it/educational-offer/laurea-magistrale-equivalent-to-master-of-science-programmes/mathematical-engineering/

For contact information see here http://www.polinternational.polimi.it/educational-offer/laurea-magistrale-equivalent-to-master-of-science-programmes/mathematical-engineering/

Find out how to apply here http://www.polinternational.polimi.it/how-to-apply/

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This MSc will give you specialist knowledge in the design, implementation and use of computing systems ranging from the components of a single processor to computer networks as vast as the internet. Read more

This MSc will give you specialist knowledge in the design, implementation and use of computing systems ranging from the components of a single processor to computer networks as vast as the internet.

You will gain a solid foundation in theoretical understanding and learn a wide variety of practical techniques that you could use in varied career settings.

Programme structure

You follow two taught semesters of lectures, tutorials, project work and written assignments, after which you will learn research methods before individual supervision for your project and dissertation.

You will choose a 'specialist area' within the programme, which will determine the choice of your optional courses. The specialist areas are:

  • Analytical and Scientific Databases
  • Computer Systems, Software Engineering, and High Performance Computing
  • Programming Languages
  • Theoretical Computer Science
  • Cyber Security and Privacy

Compulsory courses:

  • Informatics Research Review
  • Informatics Project Proposal
  • Introduction to Java Programming (for students who do not already meet the programming requirements for the taught masters)
  • Dissertation

There are more than 50 optional courses to choose from, such as:

  • Machine Learning and Pattern Recognition
  • Probabilistic Modelling and Reasoning
  • Extreme Computing
  • Bioinformatics
  • Computer Graphics
  • Computer Networking
  • Human-Computer Interaction
  • Parallel Architectures
  • Parallel Programming Languages and Systems
  • Software Architecture, Process and Management
  • Algorithmic Game Theory and its Applications
  • Computer Algebra

Career opportunities

Through this programme you will develop specialist, advanced skills in the development, construction and management of advanced computer systems. You will gain practical experience and a thorough theoretical understanding of the field making you attractive to a wide range of employers or preparing you for further academic study. Recent graduates are now working in a variety of computing roles such as software or systems, developers and engineers, analysts and applications developers for companies including Cisco, Toshiba, Microsoft, Athlon, Skyscanner, Amazon, BT, Total, Honeywell and JPMorgan Chase.



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Degree. Master of Science (two years) with a major in Computer Science and Engineering. This programme is aimed at students with a bachelor’s degree in Computer Science. Read more

Degree: Master of Science (two years) with a major in Computer Science and Engineering.

This programme is aimed at students with a bachelor’s degree in Computer Science. You will learn to master the theoretical foundations in the field and how to integrate them with other technologies.

Computer science is one of the most dynamic and expansive fields of science. In addition to having a deep understanding of the theoretical and technical foundations, professionals in this field must be able to apply the technology to challenging problems, and integrate it with other technologies. Applicants should have an adequate background in computer science and good programming skills.

The first three semesters include not only core courses in theoretical computer science and programming, but also elective courses such as artificial intelligence, databases and data mining, the design and programming of computer games, information security, advanced computer graphics, and human-computer interaction. Most courses feature lectures in theory and techniques, which are applied in practical laboratory work. Some courses also feature projects and seminars.

Five specialisations

The programme offers five specialisations:

  • Visualisation and Computer Graphics
  • Artificial Intelligence and Data Mining
  • Computer Networks, Distributed Systems and Security
  • Embedded Systems
  • Programming and Software Methods.

It is not mandatory to follow a specialisation – you may also tailor your own combination of courses, with full freedom of choice. All specialisations are offered in Linköping, except Visualisation and Computer Graphics, which is given at Campus Norrköping.

Major computer science centre

In the final semester you write a thesis, either on your own or with a fellow student. The work may be carried out in collaboration with a company, or as a research project with the university.

Linköping University is home to one of the most important centres of computer science and engineering in Northern Europe, renowned for top-quality research and education. Science Park Mjärdevi, an incubator with 300 knowledge-intensive companies where many of our alumni are employed, is adjacent to the campus.



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Data is becoming an ever increasing part of modern life, yet the talent to extract information and value from complex data is scarce. Read more

Data is becoming an ever increasing part of modern life, yet the talent to extract information and value from complex data is scarce. This Masters will provide you with a thorough grounding in state-of-the art methods for learning from data, both in terms of statistical modelling and computation. You will also gain practical hands-on experience in carrying out various data-driven analytical projects. Previous study of Statistics or Computing Science is not required.

Why this programme?

  • The University of Glasgow’s School of Mathematics and Statistics is ranked 3rd in Scotland and 11th in the UK (Complete University Guide 2017).
  • The Statistics Group at Glasgow is the largest Statistics group in Scotland and internationally renowned for its research excellence.

Programme Structure

Core courses

  • Bayesian Statistics
  • Big Data Analytics
  • Data Management and Analytics using SAS
  • Generalised Linear Models
  • Introduction to R Programming
  • Preliminary Mathematics for Statisticians 1
  • Probability 2
  • Regression Models2
  • Statistical Inference2

One Course is optional for students with sufficient background in Linear Algebra and Calculus.

Two students who have already completed an equivalent course can substitute this course by any other optional course, including optional courses offered as part of the MRes in Advanced Statistics (see the website for details).

In your project (60 credits) you will model data collected from research in environmental science, assessed by a dissertation.

Optional courses

Students choose at least two courses from group 1 and at least one course from group 2.

Group 1

  • Artificial Intelligence
  • Information Retrieval
  • Machine Learning
  • Programming

Group 2

  • Data Analysis
  • Professional Skills

Group 3

  • Biostatistics
  • Design of Experiments
  • Environmental Statistics
  • Financial Statistics
  • Functional Data Analysis
  • Multivariate Methods
  • Spatial Statistics
  • Stochastic Processes
  • Statistical Genetics
  • Time Series

 In your project (60 credits) you will tackle a complex data analytical problem or develop novel approaches to solving data analytical challenges. 

Career prospects

There is a massive shortage of data-analytical skills in the workforce. Statistician is projected to be one of the fastest-growing occupations. There is a massive shortage of data-analytical skills in the workforce. Statistician is projected to be one of the fastest-growing occupations. Statistical Analysis and Data Mining was listed by LinkedIn as the hottest skill in 2014 and came second in 2015.

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. Our recent graduates have taken up positions as Statisticians with the Scottish Government, as Advanced Analytics Analyst at Deloitte Ireland, as Consultant at the World Bank and as Research Officer at Kenya Medical Research Institute (KEMRI).



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What is the Master of Bioinformatics all about?.  Bioinformaticians are distinguished by their ability to formulate biologically relevant questions, design and implement the appropriate solution by managing and analysing high-throughput molecular biological and sequence data, and interpret the obtained results. Read more

What is the Master of Bioinformatics all about?

 Bioinformaticians are distinguished by their ability to formulate biologically relevant questions, design and implement the appropriate solution by managing and analysing high-throughput molecular biological and sequence data, and interpret the obtained results.

Structure

This interdisciplinary two-year programme focuses on acquiring

  • basic background knowledge in diverse disciplines belonging to the field of bioinformatics, including statistics, molecular biology and computer science
  • expert knowledge in the field of bioinformatics
  • programming skills
  • engineering skills

The 120-credit programme consists of a reorientation package (one semester), a common package (two semesters) and a thesis.

The Master of Bioinformatics is embedded in a strong bioinformatics research community in KU Leuven, who monthly meet at the Bioinformatics Interest Group. Bioinformatics research groups are spread over the Arenberg and Gasthuisberg campus and are located in the research departments of Microbial and Molecular Systems (M2S), Electrical Engineering (ESAT), Human Genetics, Microbiology and Immunology (REGA), Cellular and Molecular Medicine, Chemistry and Biology. Several of these bioinformatics research groups are also associated with the Flemish Institute for Biotechnology (VIB).

Is this the right programme for me? 

Are you a biochemist or molecular biologist with a keen interest in mathematics and programming? Are you a mathematician or statistician and want to apply your knowledge to complex biological questions? Do you want to develop new methods that can be used by doctors, biologists and biotechnology engineers? Then this is the right program for you!

Objectives

The student:

  • Possesses a broad knowledge of the principles of genetics, biochemistry and molecular and cellular biology that underlie the model systems, the experimental techniques, and the generation of data that are analysed and modelled in bioinformatics.
  • Possesses a broad knowledge of the basic mathematical disciplines (linear algebra, calculus, dynamical systems) that underlie mathematical and statistical modelling in bioinformatics.
  • Masters the concepts and techniques from information technology (database management, structured and object-oriented programming, semantic web technology) for the management and analysis of large amounts of complex and distributed biological and biomedical data.
  • Masters the concepts and techniques from machine learning and frequentist and Bayesian statistics that are used to analyse and model complex omics data.
  • Has acquired knowledge of the core methods of computational biology (such as sequence analysis, phylogenetic analysis, quantitative genetics, protein modelling, array analysis).
  • Has advanced interdisciplinary skills to communicate with experts in life sciences, applied mathematics, statistics, and computer science to formalise complex biological problems into appropriate data management and data analysis strategies.
  • Can - in collaboration with these experts - design complex omics experiments and analyse them independently.
  • Can independently collect and manage data from specialised literature and public databases and critically analyse and interpret this data to solve complex research questions, as well as develop tools to support these processes.
  • Investigates and understands interaction with other relevant science domains and integrate them within the context of more advanced ideas and practical applications and problem solving.
  • Demonstrates critical consideration of and reflection on known and new theories, models or interpretation within the specialty; and can efficiently adapt to the rapid evolution the life sciences, and especially in omics techniques, by quickly learning or developing new analysis strategies and incorporating them into the learned competences.
  • Presents personal research, thoughts, ideas, and opinions of proposals within professional activities in a suitable way, both written and orally, to peers and to a general public.
  • Develop and execute original scientific research and/or apply innovative ideas within research units.
  • Understands ethical, social and scientific integrity issues and responsibilities and is able to analyse the local and global impact of bioinformatics and genomics on individuals, organisations and society.

Career paths

Bioinformaticians find careers in the life sciences domain in the broadest sense: industry, the academic world, health care, etc. The expanding need for bioinformatics in biological and medical research ensures a large variety of job opportunities in fundamental and applied research. 60% of our graduates start a PhD after graduation.

 



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Informatics is the study of how natural and artificial systems store, process and communicate information. Read more

Informatics is the study of how natural and artificial systems store, process and communicate information.

Edinburgh has a long-standing tradition of world-class research and teaching in informatics, a discipline central to a new enlightenment in scholarship and learning, and critical to the future development of science, technology and society.

This is our most sought-after taught MSc. We offer a wide choice of courses, spanning established disciplines such as cognitive and computer science as well as emerging areas such as bioinformatics. The programme takes full advantage of our expertise in research and teaching, including specialisms unique to Edinburgh.

Programme structure

You follow two taught semesters of lectures, tutorials, project work and written assignments, after which you will learn research methods before individual supervision for your project and dissertation.

Compulsory courses:

  • Informatics Research Review
  • Informatics Project Proposal
  • Introduction to Java Programming (for students who do not already meet the programming requirements for the taught masters)
  • Dissertation

You will choose a ‘specialist area’ within the programme, which will determine the choice of your optional courses:

  • Analytical and Scientific Databases
  • Bioinformatics Systems and Synthetic Biology
  • Cognitive Science, Computer Systems, Software Engineering and High Performance Computing
  • Intelligent Robotics
  • Agents, Knowledge and Data
  • Machine Learning
  • Natural Language Understanding
  • Neural Computation and Neuroinformatics
  • Programming Languages
  • Theoretical Computer Science

There are 100 optional courses available to MSc Informatics students, including courses within specialist areas unique to the programme.

Career opportunities

Our graduates are well regarded by potential employers worldwide. Many go on to work in the technology industry as software engineers, IT consultants, programmers and developers, and may work with the software and hardware giants that have become household names. Others go on to further study and research. Recent graduates are now employed as software developers and engineers, programmers, games designers and analysts for companies including Airbus, Citigroup, NCR Corporation, BT and Skyscanner.



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By studying this Masters, you’ll be well placed to join one of the most performance-driven applications of computer science – the multi-billion pound global games industry. Read more

By studying this Masters, you’ll be well placed to join one of the most performance-driven applications of computer science – the multi-billion pound global games industry. As a graduate, you will work at the top-end of the games industry and will develop computer graphics on high-performance platforms, or write engines for the next generation of games.

Developed in collaboration with a prestigious steering group, this course will build on your computer science knowledge to specialise in computer graphics, where programmers must push computing resources to the limit, using deep understanding of architecture and high-performance programming to generate new levels of graphical realism and visual effects on cutting-edge hardware platforms.

You’ll gain proficiency in low-level programming, a thorough understanding of multi-core and many-core programming techniques, game engine and tool development techniques, and fundamental insight into graphics and the practical techniques used in games.

Designed to meet the needs of industry

You can be sure that what you learn will be the technical skills required by industry as this course has been developed in collaboration with a prestigious steering group from industry comprising:

Members of our steering group will contribute to the delivery of the course ensuring that you learn the latest industry developments. You’ll also have the opportunity to engage directly with the games industry, through:

  • co-curricula industry lectures
  • visits to games development companies
  • attending UK games events.

We are also a member of Game Republic, which is an industry-led professional games network that supports and promotes the Yorkshire and Northern England games sector. We hope that students of this course will take part in the Game Republic student showcase.

Specialist facilities

You will use workstations with high-end GPUs to act as DirectX12 and Vulkan games development platforms and have access to other specialist hardware including the latest Virtual Reality headsets for experimenting on. For learning games engine design and exploring new rendering techniques, students will be working with the source code of a leading game engine, Epic’s “Unreal Engine 4”.



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Scientific computing is a new and growing discipline in its own right. It is concerned with harnessing the power of modern computers to carry out calculations relevant to science and engineering. Read more

Overview

Scientific computing is a new and growing discipline in its own right. It is concerned with harnessing the power of modern computers to carry out calculations relevant to science and engineering.
By its very nature, scientific computing is a fundamentally multidisciplinary subject. The various application areas give rise to mathematical models of the phenomena being studied.

Examples range in scale from the behaviour of cells in biology, to flow and combustion processes in a jet engine, to the formation and development of galaxies. Mathematics is used to formulate and analyse numerical methods for solving the equations that come from these applications.

Implementing the methods on modern, high performance computers requires good algorithm design to produce efficient and robust computer programs. Competence in scientific computing thus requires familiarity with a range of academic disciplines. The practitioner must, of course, be familiar with the application area of interest, but it is also necessary to understand something of the mathematics and computer science involved.

Whether you are interested in fundamental science, or a technical career in business or industry, it is clear that having expertise in scientific computing would be a valuable, if not essential asset. The question is: how does one acquire such expertise?

This course is one of a suite of MScs in Scientific Computation that are genuinely multidisciplinary in nature. These courses are taught by internationally leading experts in various application areas and in the core areas of mathematics and computing science, fully reflecting the multidisciplinary nature of the subject. The courses have been carefully designed to be accessible to anyone with a good first degree in science or engineering. They are excellent preparation either for research in an area where computational techniques play a significant role, or for a career in business or industry.

Key facts:
- This course is offered in collaboration with the School of Computer Science.
- It is one of a suite of courses focusing on scientific computation.
- 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 terms of research power across the three subject areas within the School of Mathematical Sciences (pure mathematics, applied mathematics, statistics and operational research).

Modules

Advanced Techniques for Differential Equations

Computational Linear Algebra

Operations Research and Modelling

Programming for Scientific Computation

Scientific Computation Dissertation

Simulation for Computer Scientists

Stochastic Financial Modelling

Variational Methods

Vocational Mathematics

Data Mining Techniques and Applications

Mathematical Foundations of Programming

English language requirements for international students

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

Further information



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The Machine Learning MSc at UCL is a truly unique programme and provides an excellent environment to study the subject. It introduces the computational, mathematical and business views of machine learning to those who want to upgrade their expertise and portfolio of skills in this domain. Read more

The Machine Learning MSc at UCL is a truly unique programme and provides an excellent environment to study the subject. It introduces the computational, mathematical and business views of machine learning to those who want to upgrade their expertise and portfolio of skills in this domain.

About this degree

Students develop an understanding of the principles underlying the development and application of new techniques in this area, alongside an awareness of, and ability to analyse the range and scope of algorithms and approaches available, and design, develop and evaluate appropriate algorithms and methods for new problems and applications.

Students undertake modules to the value of 180 credits.

The programme consists of one core module (15 credits), five to seven optional modules (75 to 105 credits), up to two modules (30 credits) from electives, and a research project (60 credits).

Core modules

  • Supervised Learning (15 credits)

Optional modules

Students must choose 15 credits from Option Group One and a minimum of 60 credits from Option Group Two. Students must choose a further 30 credits from either Option Group Two or approved electives.

Option Group One (choose 15 credits)

  • Graphical Models (15 credits)
  • Probabilistic and Unsupervised Learning (15 credits)

Option Group Two (choose 60 to 90 credits)

  • Advanced Deep Learning and Reinforcement Learning (15 credits)
  • Advanced Topics in Machine Learning (15 credits)
  • Affective Computing and Human-Robot Interaction (15 credits)
  • Applied Machine Learning (15 credits)
  • Approximate Inference and Learning in Probabilistic Models (15 credits)
  • Bioinformatics (15 credits)
  • Information Retrieval and Data Mining (15 credits)
  • Introduction to Deep Learning (15 credits)
  • Machine Vision (15 credits)
  • Programming and Mathematical Methods for Machine Learning (15 credits)
  • Statistical Natural Language Programming (15 credits)

Please note: the availability and delivery of optional modules may vary, depending on your selection.

Students may select up to 30 credits from elective modules

A list of acceptable elective modules is available on the departmental website.

Dissertation/report

All MSc students undertake an independent research project which culminates in a dissertation of 10,000-12,000 words in the form of a project report.

Teaching and learning

The programme is delivered through a combination of lectures, seminars, class discussions and project supervision. Student performance is assessed though a combination of unseen written examination, coursework (much of which involves programming and/or data analysis), practical application, and the research project.

Further information on modules and degree structure is available on the department website: Machine Learning MSc

Careers

Graduates from this programme have an excellent employment record. Substantial sectors of UK industry, including leading, large companies already make extensive use of intelligent systems techniques in the course of their business activities, and the UK has a number of very successful developers and suppliers of the technology. Students also benefit from strong corporate and academic connections within the UCL Computer Science alumni network.

Graduates have taken machine learning research degrees in domains as diverse as robotics, music, psychology, and bioinformatics at the Universities of Basel, Cambridge, Edinburgh, Nairobi, Oxford and at UCL. Graduates have also found positions with multinational companies such as BAE Systems and BAE Detica.

Recent career destinations for this degree

  • Computer Vision Engineer, ZVR
  • Data Analyst / Data Scientist, Deloitte Data Analytics Group
  • Programmatic Yield Manager and Data Analyst, eBay
  • Data Scientist, dunnhumby
  • PhD in Computer Science, UCL

Employability

Scientific experiments and companies now routinely generate vast databases and machine learning and statistical methodologies are core to their analysis. There is a considerable shortfall in the number of qualified graduates in this area internationally. Machine Learning graduates have been in high demand for PhD positions across the sciences. In London there are many companies looking to understand their customers better who have hired our graduates. Similarly graduates now work in companies in Germany, Iceland, France and the US, amongst other places, in large-scale data analysis. The finance sector has also hired several graduates recently.

Careers data is taken from the ‘Destinations of Leavers from Higher Education’ survey undertaken by HESA looking at the destinations of UK and EU students in the 2013–2015 graduating cohorts six months after graduation.

Why study this degree at UCL?

UCL Computer Science is recognised as a world leader in teaching and research, and our Master's programmes have some of the highest employment rates and starting salaries.

We take an experimental approach to our subject, enjoy the challenge and opportunity of entrepreneurial partnerships and place a high value on our extensive range of industrial collaborations.

This MSc is one of the few leading Master's programmes entirely dedicated to machine learning. It combines a rigorous theoretical academic framework along with specific knowledge of a variety of application fields to fast-track your commercial career or to prepare for PhD research.

Research Excellence Framework (REF)

The Research Excellence Framework, or REF, is the system for assessing the quality of research in UK higher education institutions. The 2014 REF was carried out by the UK's higher education funding bodies, and the results used to allocate research funding from 2015/16.

The following REF score was awarded to the department: Computer Science

96% rated 4* (‘world-leading’) or 3* (‘internationally excellent’)

Learn more about the scope of UCL's research, and browse case studies, on our Research Impact website.



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