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Masters Degrees (Numerical Methods)

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Scientists and engineers are tackling ever more complex problems, most of which do not admit analytical solutions and must be solved numerically. Read more
Scientists and engineers are tackling ever more complex problems, most of which do not admit analytical solutions and must be solved numerically. Numerical methods can only play an even more important role in the future as we face even bigger challenges. Therefore, skilled scientific programmers are in high demand in industry and academia and will drive forward much of the future economy.

Degree information

This programme aims to produce highly computationally skilled scientists and engineers capable of applying numerical methods and critical evaluation of their results to their field of science or engineering. It brings together best practice in computing with cutting-edge science and provides a computing edge over traditional science, engineering and mathematics programmes.

Students undertake modules to the value of 180 credits.

The programme consists of six core modules (90 credits), two optional modules (30 credits) and a dissertation/report (60 credits). A Postgraduate Diploma, six core modules (90 credits), two optional modules (30 credits), is also offered.

Core modules
-Computational and Simulation Methods
-Numerical Methods
-Numerical Optimisation
-Research Computing with C++
-Research Software Engineering with Python
-Techniques of High-Performance

Optional modules - options include a wide selection of modules across UCL Engineering and UCL Mathematical & Physical Sciences.

Dissertation/report
All students undertake an independent research project project which culminates in a dissertation of 20,000 words.

Teaching and learning
The programme is delivered through a combination of lectures and hands-on programming and includes a variety of short programming projects, delivered as part of the taught component. Students are encouraged to participate in scientific seminars, for example, weekly seminars at the UCL Centre for Inverse Problems. Assessment is through examinations, assignments, small projects and the dissertation, including a computer programme.

Careers

We expect our graduates to take up exciting science and engineering roles in industry and academia with excellent prospects for professional development and steep career advancement opportunities. This degree enable students to work on cutting-edge real-life problems, overcome the challenges they pose and so contribute to advancing knowledge and technology in our society.

Employability
Students develop a comprehensive set of skills which are in high demand both in industry and academia: professional software development skills including state-of-the-art scripting and compiled languages; knowledge of techniques used in high-performance computing; understanding and an ability to apply a wide range of numerical methods and numerical optimisation; a deeper knowledge of their chosen science subject; oral and written presentational skills.

Why study this degree at UCL?

UCL has a global reputation for excellence in research and is committed to delivering impact and innovations that enhance the lives of people in the UK, across Europe and around the world. UCL is consistently placed in the global top 20 across a wide range of university rankings (currently fifth in QS World University Rankings 2014/15). Furthermore, the Thomson Scientific Citation Index shows that UCL is the 2nd most highly cited European university and 13th in the world.

Our wide-ranging expertise provides opportunities for groundbreaking interdisciplinary investigation. World-leading experts in the field and students benefit from a programme of distinguished visitors and guest speakers in many scientific seminars. In this way a network of collaborators, mentors and peers is created, which students can access in their future career.

This degree has been designed to balance a professional software development and high performance computing skills with a comprehensive selection of numerical mathematics and scientific subjects, culminating in a scientific computing dissertation project. The dual aspect of a science and computing degree enable students to tackle real-life problems in a structured and rigorous way and produce professional software for their efficient solution.

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

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

Course detail

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

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

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

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

Learning Outcomes

By the end of the course, students will have:

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

Format

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

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

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

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

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

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

Continuing

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

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

Funding Opportunities

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

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

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The Aerodynamics and Computation programme looks at the fundamentals of aerodynamics as a subject, focusing on numerical methods and the physics and computation of turbulence. Read more

Summary

The Aerodynamics and Computation programme looks at the fundamentals of aerodynamics as a subject, focusing on numerical methods and the physics and computation of turbulence.
Suitable for those from an engineering, physical sciences or mathematics background who are aiming for advanced specialisation in aerodynamics.

Modules

Compulsory modules: Aerothermodynamics; Advanced Computational Methods I (or Numerical Methods); Applications of CFD; Turbulence: Physics and Modelling; MSc Research Project

Optional modules: further module options are available

Visit our website for further information...



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This programme develops mathematical modelling skills and provides mathematical techniques required by industry. The period October to June is devoted to lectures, tutorials and practical sessions comprising the core modules. Read more
This programme develops mathematical modelling skills and provides mathematical techniques required by industry.

The period October to June is devoted to lectures, tutorials and practical sessions comprising the core modules.

This is followed by a period of about 14 weeks devoted to an individual project either in an industrial or engineering company or at the University.

Core study areas include mathematical modelling, regular and chaotic dynamics, programming and numerical methods, advanced reliability, availability and maintainability, elements of partial differential equations, static and dynamic optimisation and fluid mechanics.

See the website http://www.lboro.ac.uk/study/postgraduate/programmes/departments/mathematics/industrial-maths-modelling/

Programme modules

Compulsory Modules:
Semester 1
- Mathematical Modelling I
- Regular and Chaotic Dynamics
- Programming and Numerical Methods
- Advanced Reliability, Availability and Maintainability

Semester 2
- Mathematical Modelling II
- Elements of Partial Differential Equations
- Static and Dynamic Optimisation
- Fluid Mechanics

Assessment

A combination of written examinations, reports, individual and group projects, and verbal presentations.

Careers and further Study

Graduate employment over a wide range of industries encompassing aerospace, automotive electronics, and computer interests as well as software houses, insurance companies, and research establishments and institutions.

Scholarships and sponsorships

A limited number of scholarships are available for this programme as well as the loyalty bonus scheme which reduces fees for Loughborough graduates.

Why choose mathematics at Loughborough?

Mathematics at Loughborough has a long history of innovation in teaching, and we have a firm research base with strengths in both pure and applied mathematics as well as mathematics education.

The Department comprises more than 34 academic staff, whose work is complemented and underpinned by senior visiting academics, research associates and a large support team.

The programmes on offer reflect our acknowledged strengths in pure and applied research in mathematics, and in some cases represent established collaborative training ventures with industrial partners.

- Mathematics Education Centre (MEC)
The Mathematics Education Centre (MEC) at Loughborough University is an internationally renowned centre of research, teaching, learning and support. It is a key player in many high-profile national initiatives.
With a growing number of academic staff and research students, the MEC provides a vibrant, supportive community with a wealth of experience upon which to draw.
We encourage inquiries from students who are interested in engaging in research into aspects of learning and teaching mathematics at Masters, PhD and Post Doc levels. Career prospects With 100% of our graduates in employment and/or further study six months after graduating, career prospects are excellent. Graduates go on to work with companies such as BAE Systems, Citigroup, Experian, GE Aviation, Mercedes Benz, Nuclear Labs USA and PwC.

- Career prospects
With 100% of our graduates in employment and/or further study six months after graduating, career prospects are excellent. Graduates
go on to work with companies such as BAE Systems, Citigroup, Experian, GE Aviation, Mercedes Benz, Nuclear Labs USA and PwC.

Find out how to apply here http://www.lboro.ac.uk/study/postgraduate/programmes/departments/mathematics/industrial-maths-modelling/

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

Swansea University has gained a significant international profile as one of the key international centres for research and training in computational mechanics and engineering. As a student on the Master's course in Erasmus Mundus Computational Mechanics, you will be provided with in-depth, multidisciplinary training in the application of the finite element method and related state-of-the-art numerical and computational techniques to the solution and simulation of highly challenging problems in engineering analysis and design.

Key Features of Erasmus Mundus Computational Mechanics MSc

The Zienkiewicz Centre for Computational Engineering is acknowledged internationally as the leading UK centre for computational engineering research. It represents an interdisciplinary group of researchers who are active in computational or applied mechanics. It is unrivalled concentration of knowledge and expertise in this field. Many numerical techniques currently in use in commercial simulation software have originated from Swansea University.

The Erasmus Mundus MSc Computational Mechanics course is a two-year postgraduate programme run by an international consortium of four leading European Universities, namely Swansea University, Universitat Politècnica de Catalunya (Spain), École Centrale de Nantes (France) and University of Stuttgart (Germany) in cooperation with the International Centre for Numerical Methods in Engineering (CIMNE, Spain).

As a student on the Erasmus Mundus MSc Computational Mechanics course, you will gain a general knowledge of the theory of computational mechanics, including the strengths and weaknesses of the approach, appreciate the worth of undertaking a computational simulation in an industrial context, and be provided with training in the development of new software for the improved simulation of current engineering problems.

In the first year of the Erasmus Mundus MSc Computational Mechanics course, you will follow an agreed common set of core modules leading to common examinations in Swansea or Barcelona. In addition, an industrial placement will take place during this year, where you will have the opportunity to be exposed to the use of computational mechanics within an industrial context. For the second year of the Erasmus Mundus MSc Computational Mechanics, you will move to one of the other Universities, depending upon your preferred specialisation, to complete a series of taught modules and the research thesis. There will be a wide choice of specialisation areas (i.e. fluids, structures, aerospace, biomedical) by incorporating modules from the four Universities. This allows you to experience postgraduate education in more than one European institution.

Modules

Modules on the Erasmus Mundus MSc Computational Mechanics course can vary each year but you could expect to study the following core modules (together with elective modules):

Numerical Methods for Partial Differential Equations
Continuum Mechanics
Advanced Fluid Mechanics
Industrial Project
Finite Element Computational Analysis
Entrepreneurship for Engineers
Finite Element in Fluids
Computational Plasticity
Fluid-Structure Interaction
Nonlinear Continuum Mechanics
Computational Fluid Dynamics
Dynamics and Transient Analysis
Reservoir Modelling and Simulation

Accreditation

The Erasmus Mundus Computational Mechanics course is accredited by the Joint Board of Moderators (JBM).

The Joint Board of Moderators (JBM) is composed of the Institution of Civil Engineers (ICE), the Institution of Structural Engineers (IStructE), the Chartered Institution of Highways and Transportation (CIHT), and the Institute of Highway Engineers (IHE).

This degree is accredited as meeting the requirements for Further Learning for a Chartered Engineer (CEng) for candidates who have already acquired an Accredited CEng (Partial) BEng(Hons) or an Accredited IEng (Full) BEng/BSc (Hons) undergraduate first degree.

See http://www.jbm.org.uk for further information.

This degree has been accredited by the JBM under licence from the UK regulator, the Engineering Council.

Accreditation is a mark of assurance that the degree meets the standards set by the Engineering Council in the UK Standard for Professional Engineering Competence (UK-SPEC). An accredited degree will provide you with some or all of the underpinning knowledge, understanding and skills for eventual registration as an Incorporated (IEng) or Chartered Engineer (CEng). Some employers recruit preferentially from accredited degrees, and an accredited degree is likely to be recognised by other countries that are signatories to international accords.

Links with Industry

On the Erasmus Mundus MSc Computational Mechanics course, you will have the opportunity to apply your skills and knowledge in computational mechanics in an industrial context.

As a student on the Erasmus Mundus MSc Computational Mechanics course you will be placed in engineering industries, consultancies or research institutions that have an interest and expertise in computational mechanics. Typically, you will be trained by the relevant industry in the use of their in-house or commercial computational mechanics software.

You will also gain knowledge and expertise on the use of the particular range of commercial software used in the industry where you are placed.

Careers

The next decade will experience an explosive growth in the demand for accurate and reliable numerical simulation and optimisation of engineering systems.

Computational mechanics will become even more multidisciplinary than in the past and many technological tools will be, for instance, integrated to explore biological systems and submicron devices. This will have a major impact in our everyday lives.

Employment can be found in a broad range of engineering industries as this course provides the skills for the modelling, formulation, analysis and implementation of simulation tools for advanced engineering problems.



Student Quotes

“I gained immensely from the high quality coursework, extensive research support, confluence of cultures and unforgettable friendship.”

Prabhu Muthuganeisan, MSc Computational Mechanics

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The Masters in Mathematics/Applied Mathematics offers courses, taught by experts, across a wide range. Mathematics is highly developed yet continually growing, providing new insights and applications. Read more
The Masters in Mathematics/Applied Mathematics offers courses, taught by experts, across a wide range. Mathematics is highly developed yet continually growing, providing new insights and applications. It is the medium for expressing knowledge about many physical phenomena and is concerned with patterns, systems, and structures unrestricted by any specific application, but also allows for applications across many disciplines.

Why this programme

◾Mathematics at the University of Glasgow is ranked 3rd in Scotland (Complete University Guide 2017).
◾The School has a strong international reputation in pure and applied mathematics research and our PGT programmes in Mathematics offer a large range of courses ranging from pure algebra and analysis to courses on mathematical biology and fluids.
◾You will be taught by experts across a wide range of pure and applied mathematics and you will develop a mature understanding of fundamental theories and analytical skills applicable to many situations.
◾You 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 in Mathematics/Applied Mathematics include lectures, laboratory classes, seminars and tutorials and allow students the opportunity to take part in project work.

If you are studying for the MSc you will take a total of 120 credits from a mixture of Level-4 Honours courses, Level-M courses and courses delivered by the Scottish Mathematical Sciences Training Centre (SMSTC).

You will take courses worth a minimum of 90 credits from Level-M courses and those delivered by the SMSTC. The remaining 30 credits may be chosen from final-year Level-H courses. The Level-M courses offered in a particular session will depend on student demand. Below are courses currently offered at these levels, but the options may vary from year to year.

Level-H courses (10 or 20 credits)
◾Algebraic & geometric topology
◾Continuum mechanics & elasticity
◾Differential geometry
◾Fluid mechanics
◾Functional analysis
◾Further complex analysis
◾Galois theory
◾Mathematical biology
◾Mathematical physics
◾Numerical methods
◾Number theory
◾Partial differential equations
◾Topics in algebra.

Level-M courses (20 credits)
◾Advanced algebraic & geometric topology
◾Advanced differential geometry & topology
◾Advanced functional analysis
◾Advanced methods in differential equations
◾Advanced numerical methods
◾Biological & physiological fluid mechanics
◾Commutative algebra & algebraic geometry
◾Elasticity
◾Further topics in group theory
◾Lie groups, lie algebras & their representations
◾Magnetohydrodynamics
◾Operator algebras
◾Solitons
◾Special relativity & classical field theory.

SMSTC courses (20 credits)
◾Advanced Functional Analysis
◾Advanced Mathematical Methods

The project titles are offered each year by academic staff and so change annually.

Career prospects

Career opportunities are diverse and varied and include academia, teaching, industry and finance.

Graduates of this programme have gone on to positions such as:
Maths Tutor at a university.

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There is a growing need for qualified professionals with expertise in environmental modelling. The UCL Environmental Modelling MSc is a cross-disciplinary degree that provides rigorous technical and scientific training for the next generation of environmental modelling professionals. Read more
There is a growing need for qualified professionals with expertise in environmental modelling. The UCL Environmental Modelling MSc is a cross-disciplinary degree that provides rigorous technical and scientific training for the next generation of environmental modelling professionals.

Degree information

You will gain a well-rounded training in the role, implementation and application of models in environmental science. Core modules provide a critical perspective on model-based science, and introduce essential computational and numerical methods. The programme is contextualised with reference to the challenges of understanding both natural and human-induced changes to a variety of environmental systems.

Students take modules to the value of 180 credits. The programme consists of four core modules (60 credits), optional modules (60 credits) and a research dissertation (60 credits). A Postgraduate Diploma (120 credits, full-time nine months, part-time two years) is offered. A Postgraduate Certificate (60 credits, full-time 12 weeks, part-time one year) is offered.

Core modules
-Models in Environmental Science
-Global Environmental Change
-Scientific Computing
-Analytical and Numerical Methods

Optional modules - options may include:
-Climate Modelling
-Coastal Change
-Environmental GIS
-Impacts of Climate Change on Hydro-Ecological Systems
-Lakes
-Ocean Circulation and Climate Change
-Surface Water Modelling
-Terrestrial Carbon: Monitoring and Modelling
-Other MSc modules offered across UCL may be taken at the discretion of the MSc convenor

Dissertation/report
All students undertake an independent research project, culminating in a dissertation of approximately 12,000 words and an oral presentation.

Teaching and learning
The programme is delivered through a combination of lectures, seminars, tutorials, and laboratory and computer-based practical classes. Assessment is through independent project work, practical-based and written coursework, written examinations and the dissertation.

Careers

The programme has been designed to provide an ideal foundation for PhD research, or for employment with environmental monitoring and protection agencies, industry and environmental consultancies. Graduates have gone on to careers as management consultants, business analysts and university researchers.

Top career destinations for this degree:
-Research Fellow, University of Girona and studying PhD Sanitas, Universitat de Girona (University of Girona)
-Risk Analyst, Canopius

Employability
Modelling was identified as the highest priority UK skills gap in a government review of the environmental sector. This MSc programme exposes students to the full range of environmental modelling which places graduates in a strong position to find employment. We anticipate that graduates of this MSc are either employed in the private environmental consulting sector or undertake a PhD.

Why study this degree at UCL?

The Environmental Modelling MSc is run by UCL Geography which enjoys an outstanding international reputation for its research and teaching. Research groups contributing to the MSc include those concerned with environmental modelling and observation, past climates, and recent environmental change and biodiversity.

The programme draws on the unrivalled strengths of UCL in environment modelling. Our expertise encompasses state-of-the-art global climate models, regional ocean models, advanced hydrodynamic and hydrological simulations, palaeoclimate reconstruction over geological to recent historical timescales, earth observation-derived vegetation and carbon cycle modelling, and model-based assessment of climate change impacts on coastal, estuarine and freshwater systems.

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The programme provides graduates with strong mathematical skills, the necessary computational techniques and finance background relevant to subsequent employment in a sector of finance such as investment banks, hedge funds, insurance companies and the finance departments of large corporations where mathematics plays a key role. Read more
The programme provides graduates with strong mathematical skills, the necessary computational techniques and finance background relevant to subsequent employment in a sector of finance such as investment banks, hedge funds, insurance companies and the finance departments of large corporations where mathematics plays a key role.

The depth of the mathematics taught should enable graduates to pursue research careers in stochastic analysis, financial mathematics or other relevant areas.

The period October to June is devoted to lectures, tutorials and practical sessions comprising the core and optional modules. This is followed by a period of about 14 weeks devoted to an individual project.

Core study areas include measure theory and martingales, stochastic models in finance, stochastic calculus and theory of stochastic pricing and a research project.

Optional study areas include programming and numerical methods, regular and chaotic dynamics, financial economics, functional analysis, elements of PDEs, static and dynamic optimisation, asset management and derivatives, and corporate finance

See the website http://www.lboro.ac.uk/study/postgraduate/programmes/departments/mathematics/mathematical-finance/

Programme modules

Semester 1:
Compulsory Modules
- Introduction to Measure Theory and Martingales
- Stochastic Models in Finance

Optional Modules (choose two)
- Programming and Numerical Methods
- Regular and Chaotic Dynamics
- Financial Economics

Semester 2:
Compulsory Modules
- Stochastic Calculus and Theory of Stochastic Pricing
- Research Project

Optional Modules (choose three)
- Functional Analysis
- Elements of PDEs
- Static and Dynamic Optimisation
- Either Asset Management and Derivatives or Corporate Finance

Assessment

A combination of written examinations, reports, individual and group projects, and verbal presentations.

Careers and further study

This programme may lead to a wide range of employment within industry, the financial sectors, and research establishments. It may also provide an ideal background for postgraduate research in Stochastic Analysis, Probability Theory, Mathematical Finance and other relevant areas.

Scholarships and sponsorships

A number of part-fee studentships may be available to appropriately qualified international students.

Why choose mathematics at Loughborough?

Mathematics at Loughborough has a long history of innovation in teaching, and we have a firm research base with strengths in both pure and applied mathematics as well as mathematics education.

The Department comprises more than 34 academic staff, whose work is complemented and underpinned by senior visiting academics, research associates and a large support team.

The programmes on offer reflect our acknowledged strengths in pure and applied research in mathematics, and in some cases represent established collaborative training ventures with industrial partners.

- Mathematics Education Centre (MEC)
The Mathematics Education Centre (MEC) at Loughborough University is an internationally renowned centre of research, teaching, learning and support. It is a key player in many high-profile national initiatives.
With a growing number of academic staff and research students, the MEC provides a vibrant, supportive community with a wealth of experience upon which to draw.
We encourage inquiries from students who are interested in engaging in research into aspects of learning and teaching mathematics at Masters, PhD and Post Doc levels. Career prospects With 100% of our graduates in employment and/or further study six months after graduating, career prospects are excellent. Graduates go on to work with companies such as BAE Systems, Citigroup, Experian, GE Aviation, Mercedes Benz, Nuclear Labs USA and PwC.

- Career prospects
With 100% of our graduates in employment and/or further study six months after graduating, career prospects are excellent. Graduates
go on to work with companies such as BAE Systems, Citigroup, Experian, GE Aviation, Mercedes Benz, Nuclear Labs USA and PwC.

Find out how to apply here http://www.lboro.ac.uk/study/postgraduate/programmes/departments/mathematics/mathematical-finance/

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The development of new materials lies at the heart of many of the technological challenges we currently face, for example creating advanced materials for energy generation. Read more

Overview

The development of new materials lies at the heart of many of the technological challenges we currently face, for example creating advanced materials for energy generation. Computational modelling plays an increasingly important role in the understanding, development and optimisation of new materials. This four year Doctoral Training Programme on computational methods for material modelling aims to train scientists not only in the use of existing modelling methods but also in the underlying computational and mathematical techniques. This will allow students to develop and enhance existing methods, for instance by introducing new capabilities and functionalities, and also to create innovative new software tools for materials modelling in industrial and academic research. The first year of the CDT is a materials modelling option within the MPhil in Scientific Computing (please see the relevant entry) at the University of Cambridge and a range of additional training elements.

The MPhil in Scientific Computing is administered by the Department of Physics, but it serves the training needs of the Schools of Physical Sciences, Technology and Biological Sciences. The ability to have a single Master’s course for such a broad range of disciplines and applications is achieved by offering core (i.e. common for all students) numerical and High Performance Computing (HPC) lecture courses, and complementing them with elective courses relevant to the specific discipline applications.

In this way, it is possible to generate a bespoke training portfolio for each student without losing the benefits of a cohort training approach. This bespoke course is fully flexible in allowing each student to liaise with their academic or industrial supervisor to choose a study area of mutual interest.

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

Learning Outcomes

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

Teaching

The first year of the CDT has a research as well as a taught element. The students attend lecture courses during the first five months (October-February) and then they will undertake a substantial Research Project over the next 6 months (from March to the end of August) in a participating Department. The research element aims to provide essential skills for a successful completion of the PhD, as well as to assess and enhance the research capacity of the students. It is based on a materials science topic which is studied by means of scientific computation. Research project topics will be provided by academic supervisors or by the industrial partners. Most of the projects are expected to make use the University’s High Performance Computing Service (for which CPU time for training and research has been budgeted for every student).

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

The core courses are on topics of high-performance scientific computing and advanced numerical methods and techniques; they are taught and examined during the first five months (October-February). Their purpose is to provide the students with essential background knowledge for completing their theses and for their general education in scientific computing.

Appropriate elective courses are selected from Master’s-level courses offered by the Departments of the School of Physical Sciences, Technology or Biological Sciences. The choice of courses will be such as to provide the students with essential background knowledge for completing their theses and for their general education in the materials science application of the project. They are decided in consultation with the project supervisor.

Depending on the materials science application of the research topic, students will follow one of the following two numerical methodology options: a) Continuum methods based on systems of partial differential equations (PDEs, e.g. finite-difference, element or volume methods); or b) atomistic approaches, which can be based on classical particle-based modelling (e.g. molecular dynamics) or on electronic structure- based methods (e.g. density functional theory). The students who take the atomistic modelling options will attend a 12-lecture course before continuing to classical particle-based methods or electronic structure methods. Irrespective of the numerical methodology option, students will attend lecture courses on High Performance Computing topics and elements of Numerical Analysis.

In addition to the comprehensive set of Masters-level courses provided by the MPhil and across the University in the field, which will be available to the CDT students, it will also be possible for students to take supplementary courses (not for examination) at undergraduate level, where a specific need is identified, in order to ensure that any prerequisite knowledge for the Masters courses is in place.

Moreover, depending on their background and circumstances, students may be offered places in the EPSRC-funded Autumn Academy, which takes place just before the start of the academic year (two weeks in September).

Funding Opportunities

Studentships funded by EPSRC and/or Industrial and other partners are available subject to eligibility criteria.

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

Find out how to apply here http://www.graduate.study.cam.ac.uk/courses/directory/pcphpdcms/apply

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

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Applied Mathematics is concerned with mathematical methods used in industry, science, business and engineering. Studying this subject at doctoral level is an opportunity to become an specialist in the mathematics that powers business and society. Read more
Applied Mathematics is concerned with mathematical methods used in industry, science, business and engineering. Studying this subject at doctoral level is an opportunity to become an specialist in the mathematics that powers business and society.

As a researcher in the School of Mathematics and Physics, you have the opportunity to work with specialists in the field and may have the chance to develop national and international collaborations.

Research in the School follows two distinct strands: computational physics/applied mathematics and pure mathematics. Research in applied mathematics is focused on the development of numerical methods and algorithms for solving various equations found in materials science, specifically in the field of nanomaterials. This includes advanced parallelisation and adaptation of the methods for modern supercomputers.

Research Areas, Projects & Topics

Main Research Areas:
-Numerical Methods for non-linear Partial Differential Equations in Materials Science
-High Performance Computing in Materials Science

For information about the School’s research activity please visit: http://www.lincoln.ac.uk/home/smp/research/

How You Study

You can benefit from specialist computational facilities, training programmes to enhance your research skills and support from dedicated academic supervisors. You will be supported and encouraged to submit papers to international scientific journals, present your findings at conferences and share knowledge with colleagues across the University.

Due to the nature of postgraduate research programmes, the vast majority of your time will be spent in independent study and research. You will have meetings with your academic supervisors, however the regularity of these will vary depending on your own individual requirements, subject area, staff availability and the stage of your programme.

How You Are Assessed

A PhD is usually awarded based on the quality of your thesis and your ability in an oral examination (viva voce) to present and successfully defend your chosen research topic.

Career and Personal Development

Applied Mathematics students have the opportunity to develop the problem solving skills that may lead to careers in academia, research or industry. 

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An MSc by Research in Applied Mathematics gives students the opportunity to conduct research into areas of mathematics with practical applications in business and industry. Read more
An MSc by Research in Applied Mathematics gives students the opportunity to conduct research into areas of mathematics with practical applications in business and industry.

As a researcher in the School of Mathematics and Physics, you have the opportunity to work with specialists in the field and may have the chance to develop national and international collaborations.

Research in the School follows two distinct strands: computational physics/applied mathematics and pure mathematics. Research in applied mathematics is focused on the development of numerical methods and algorithms for solving various equations found in materials science, specifically in the field of nanomaterials. This includes advanced parallelisation and adaptation of the methods for modern supercomputers.

Research Areas, Projects & Topics

Main Research Areas:
-Numerical Methods for Non-Liner Partial Differential Equations in Materials Science
-High Performance Computing in Materials Science.

For detailed information about the School’s research activity please visit: http://www.lincoln.ac.uk/home/smp/research/

How You Study

You can benefit from specialist computational facilities, training programmes to enhance your research skills and support from dedicated academic supervisors. You will be supported and encouraged to submit papers to international scientific journals, present your findings at conferences and share knowledge with colleagues across the University.

Due to the nature of postgraduate research programmes, the vast majority of your time will be spent in independent study and research. You will have meetings with your academic supervisor, however the regularity of these will vary depending on your own individual requirements, subject area, staff availability and the stage of your programme.

How You Are Assessed

The MSc by Research involves writing a Master's thesis under the supervision of a member of academic staff on a topic to be agreed with your supervisor. The MSc by Research is usually awarded based on the quality of your thesis and your ability in an oral examination (viva voce) to present and successfully defend your chosen research topic.

Career and Personal Development

Applied Mathematics students have the opportunity to develop the problem solving skills that may lead to careers in academia, research or industry. 

The University Careers and Employability Team offer qualified advisors who can work with you to provide tailored, individual support and careers advice during your time at the University. As a member of our alumni we also offer one-to-one support in the first year after completing your course, including access to events, vacancy information and website resources; with access to online vacancies and virtual and website resources for the following two years.

This service can include one-to-one coaching, CV advice and interview preparation to help you maximise your future opportunities.
The service works closely with local, national and international employers, acting as a gateway to the business world.

Visit our Careers Service pages here http://bit.ly/1lAS1Iz.

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Programme Description. This one-year programme is designed to equip graduates and professionals with a broad and robust training on modern power engineering technologies, with a strong focus on renewable energy conversion and smart grids. Read more

Programme Description

This one-year programme is designed to equip graduates and professionals with a broad and robust training on modern power engineering technologies, with a strong focus on renewable energy conversion and smart grids. It is suitable for recent graduates who wish to develop the specialist knowledge and skills relevant to this industry and is also suitable as advanced study in preparation for research work in an academic or industrial environment.

In semesters 1 and 2, the programmes comprises a mixture of taught courses, workshops and a group design project, led by leading experts in the field, covering the key topics in power systems, electrical machines and power electronics. The final part of the programme is an individual dissertation, which provides a good opportunity for students to apply their acquired skills to real problems in electrical power engineering.

This one year programme at the University of Edinburgh will immerse the students in the most current developments in the area of Electrical Power Engineering, through a combination of taught modules, workshops, a research dissertation, and a range of supporting activities delivered by internationally leading experts in the field. The programme develops through the year from advanced fundamental topics and research tools and techniques in electrical power engineering, to specialist courses on emerging technologies and advanced numerical methods for power engineering problems, and culminates in the summer dissertation project where the acquired skills in various areas are put into practice in application to an actual power engineering problem.

Topics covered within the individual courses of the programme, include (but are not limited to):

Fundamental and emerging power engineering technologies

Advanced numerical methods in application to electrical power engineering problems

Modern power conversion components & systems

Integration of renewable energy in the power system

Distributed energy resources

Electrical engineering aspects of energy storage

Power, telecommunications & control aspects of smart grids

Research and innovation management techniques.

In addition, our MSc students actively engage in research as part of their dissertation projects either within the Institute for Energy Systems or with industry, with some joining our PhD community afterwards.

Programme Structure

This programme is delivered over 12 months, with two semesters of taught courses, followed by a research project leading to the submission of a Master’s Thesis.

Semester 1

Power Electronics, Machines & Systems

Power Engineering Research Techniques

Energy & Environmental Economics

Technologies for Sustainable Energy

Semester 2

Power Conversion and Control

Power Systems Engineering & Economics

Distributed Energy Resources and Smart Grids

Research Project

Electrical Power Engineering Dissertation The above courses correspond to 120 credits of taught material, plus 60 credits of a research project

Learning Outcomes

The main objective of the programme is to train the next generation of electrical power engineers who:

are aware of the most recent, cutting edge developments in power engineering;

have skills and training needed in both industrial and academic settings;

are able to tackle the global energy trilemma of supplying secure, equitable and environmentally sustainable energy, while appreciating the technical, social and economic challenges faced in both developed and developing countries.

Career Opportunities

Governments worldwide are putting in place plans to decarbonise and modernise their electricity sector. A transition to a green economy will require a highly skilled workforce led by electrical power engineers with a solid academic background, an appreciation of the trajectory of the industry and an understanding of the challenges and implications brought about by the introduction of new power technologies.

According to the Institution for Engineering & Technology (IET): “The business of managing and distributing power in the UK is beginning to undergo revolutionary changes and [power] engineers are the people who will play a pivotal role in keeping the lights on”. This also holds true in many other developed and developing countries in the world.

Power engineers are employed in public/governmental organisations as well as in the private sector and cover areas spanning from generation, to conversion and transmission of electrical power, design and manufacturing of power components and systems, and energy policy and commerce. In the UK, experienced, chartered power engineers can earn around £45,000 a year on average*.

The programme will run in a close association with other activities within the broader Electrical Engineering programme within the School, including networking events, industrial presentations and seminars. It will benefit from the current strong connections with industry (coordinated by the Student Industry Liaison Manager, and existing research associations and consortia (such as the EPSRC Centre for Energy Systems Integration).



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The degree includes components necessary to provide the areas of subject-specific expertise and research methods training identified by the ESRC as essential for recognition for the ‘1 + 3’ (MA and PhD) programme. Read more
The degree includes components necessary to provide the areas of subject-specific expertise and research methods training identified by the ESRC as essential for recognition for the ‘1 + 3’ (MA and PhD) programme.

The full-time MA starts in October and continues in three consecutive terms over 12 months. The part-time MA takes place over 24 months with candidates taking an equal balance of credits in each year of study.

You will be required to complete 180 credits for the award of an MA. The programme is comprised of the following modules.

The degree follows a logical progression in that ‘Perspectives on Social Research’ and ‘Statistical Exploration and Reasoning’ are taught in the first term. 'Research Design and Process' is also taught in the first term to help students develop a research proposal for dissertation. These modules provide introductions to the specific areas and are intended to provide a foundation for later work. In term two, ‘Quantitative Research Methods in the Social Sciences’,‘Qualitative Research Methods in the Social Sciences’ and 'Policy Related and Evaluation Research' are taught. These modules develop the work introduced in the first term.

The subject specific module – Theorising Crime and Criminal Justice - run through terms one and two and provide the ‘spine’ to the programme, bringing together issues identified in other modules. These modules also specifically relate more generic issues arising in research to subject-specific questions.

Breadth

The programme is broadly based, covering conceptual and practical underpinnings and implications of research, and covering various research techniques and the rationale behind them. It enable students to develop essential skills in both quantitative and qualitative work and to apply those skills to specific criminological issues.

Depth

The programme covers issues in depth, as appropriate to a Master’s programme. The depth at which students learn progressively increases, with the dissertation providing an opportunity for an in-depth piece of scholarly work at an advanced level.

These are the knowledge and skills students who complete their training in research methods are expected to have acquired and to be able to apply:
-Comprehension of principles of research design and strategy, including an understanding of how to formulate researchable problems and an appreciation of alternative approaches to research problems.
-Competence in understanding, and applying appropriately in a specific subject area, a range of research methods and tools, including essential qualitative and quantitative techniques.
-Capabilities for managing research, including managing data, and conducting and disseminating research in such a way that is consistent with both professional practice and principles of research ethics and risk assessment.

In addition, students are expected to have acquired or further developed a range of transferable employment-related key skills:
-The ability to evaluate and synthesise information obtained from a variety of sources (written, electronic, oral, visual); to communicate relevant information in a variety of ways and to select the most appropriate means of communication relative to the specific task. Students will also be able to communicate their own formulations in a clear and accessible way; they will be able to respond effectively to others and to reflect on and monitor the use of their communication skills.
-The ability to read and interpret complex statistical tables, graphs and charts; to organize, classify and interpret numerical data; to make inferences from sets of data; to design a piece of research using advanced techniques of data analysis; and an appreciation of the scope and applicability of numerical data.
-Competence in using information technology including the ability to word-process, to use at least one quantitative and one qualitative computer software package effectively; to use effective information storage and retrieval; and to use web-based resources.
-The ability to plan work with others, to take a lead role in group work when required, to establish good working relationships with peers, to monitor and reflect on group work (including the student’s own group-work skills) and to take account of external feedback on contributions to group work, and on the group work process as a whole.
-Effective time-management, working to prescribed deadlines.
-The ability to engage in different forms of learning, to seek and to use feedback from both peers and academic staff, and to monitor and critically reflect on the learning process.

Subject-specific learning outcomes based on their ‘spine’ module as follows:
-An advanced knowledge of the relative strengths and weaknesses of core criminology concepts and principles – the social problem of crime and the politics and practice of criminal justice ; the construction and deconstruction of what constitutes crime.
-A clear, systematic and advanced level of understanding criminological theories and their application to criminal behaviour, criminal justice and crime control.
-An advanced understanding of key ideological and theoretical perspectives in criminology – e.g. the shift from social theories of ‘deviance’ to struggles for ‘social justice’.
-An advanced knowledge of key phenomena in criminological analysis, particularly the significance of criminological analysis and contemporary national and international issues that are redefining the study of crime, criminal behaviour and crime control.
-An advanced knowledge of the functions and practices of criminal justice as well as the relationship of these practices to political concerns of crime, disorder and security.

An appreciation of how particular criminal justice policies may be experienced by different social groups.

Course modules

Typical modules outlined below are those that were available to students studying this programme in previous years.
-Perspectives on Social Research (15 Credits)
-Statistical Exploration and Reasoning (15 Credits)
-Research Design and Process (15 credits)
-Qualitative Research Methods in Social Science (15 credits)
-Quantitative Research Methods in Social Science (15 credits)
-Theorising Crime and Criminal Justice (30 credits)
-Policy Related and Evaluation Research (15 credits)
-Dissertation (60 Credits)

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This programme is recognised by the ESRC as a research training programme designed to provide participants with a sound background on overall research design and the most up-to-date training in methods and data collection and analysis. Read more
This programme is recognised by the ESRC as a research training programme designed to provide participants with a sound background on overall research design and the most up-to-date training in methods and data collection and analysis.

The core elements of this programme are delivered by staff from across the College of Social Sciences, many of them engaged in cutting-edge research in their own fields.

The MA programme includes assessed core modules and short courses (120 credits) and the completion of a 14,000 word dissertation (60 credits), while the Postgraduate Diploma includes the assessed courses only (120 credits).

Modules

Introduction to Social Research
This module aims to provide a general introduction to studying and research methods and prepares you for your dissertation, emphasising key skills such as searching literature, finding datasets and presenting and criticising arguments. It also covers ethics of research, the role of theory and philosophical bases for understanding the social world.

Research Design
This module links the introductory module and data collection module through consideration of research design, questions, warranting practices and sampling methods. All the elements of research design are linked into an over-arching theme of the full cycle of research activity.

Social Research Methods I
This module introduces the principles and practices of data collection and explores rationales of the various methods. It will focus on the different stages of data collection, including various methods used to gather textual and numerical data.

Social Research Methods II
This module introduces students to a range of approaches for analysing and handling data. It will include covering statistical methods for quantitative data and methodological approaches for qualitative data. It emphasises that the method of analysis is not determined by the method of collection.

British Social Policy - Beyond Welfare?
This module provides students with an understanding of recent trends in social policy development and of the current social and economic context of policy making in the UK. The question underpinning the module is 'Where is British Social Policy heading?'

Researching Social Policy
This module is concerned with the politics of social research, rather than research methods and methodology. It addresses issues such as: how are certain topics identified as subjects for research, how is research commissioned and funded, and what are the relationships between research and the policy process. It draws on real-life experiences of doing research and being researched to explore these issues.

The modules on Social Research Methods I and Social Research Methods II cover a wide range of approaches, including the 'qualitative' traditions, plus mixed methods.

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The basis of natural sciences is the modelling of phenomena and solving these models. The Master’s programme in theoretical and computational methods will give you a strong basis in the theoretical methods, modelling, and mathematical and numerical analysis within physics, mathematics, chemistry and/or computer science. Read more
The basis of natural sciences is the modelling of phenomena and solving these models. The Master’s programme in theoretical and computational methods will give you a strong basis in the theoretical methods, modelling, and mathematical and numerical analysis within physics, mathematics, chemistry and/or computer science. The special feature of this programme is that you can combine the above disciplines into a comprehensive programme. It is well suited for the needs of basic research and for many fields of application. This programme requires a strong commitment from you to develop your own skills and plan your degree. You can tailor your programme according to your existing knowledge and interests, in cooperation with the programme professors.

The programme’s strong scientific emphasis makes it a natural gateway to further studies in physics, mathematics, chemistry, and computer science. This will usually take place within one of the research groups working on the Kumpula campus.

Upon completing the Master’s programme, you will:
-Have a solid basis of skills in your chosen scientific field.
-Have good skills in analytical and computational thinking and deduction.
-Be able to apply theoretical and computational methods to the analysis and understanding of problems in various fields.
-Be able to generalise information on scientific phenomena, and identify the inner relationships.
-Be able to create mathematical models of natural phenomena.
-Be able to solve the models, both analytically and numerically.

As a graduate of this Master’s programme you can work as an expert in many kinds of scientific jobs in the private and the public sectors. The employment rate in this field is good.

The University of Helsinki will introduce annual tuition fees to foreign-language Master’s programmes starting on August 1, 2017 or later. The fee ranges from 13 000-18 000 euros. Citizens of non-EU/EEA countries, who do not have a permanent residence status in the area, are liable to these fees. You can check this FAQ at the Studyinfo website whether or not you are required to pay tuition fees: https://studyinfo.fi/wp2/en/higher-education/higher-education-institutions-will-introduce-tuition-fees-in-autumn-2017/am-i-required-to-pay-tuition-fees/

Programme Contents

The special feature of this programme is its great scope: it consists of several modules in physics, mathematics, chemistry, and/or computer science. Out of these, you may select a suitable group of subjects according to your interests and the courses you took for your Bachelor's degree. The programme incorporates modules from e.g. the following areas:
-Theoretical physics
-Mathematics
-Cosmology and particle physics
-Computational physics
-Physical chemistry
-Laser spectroscopy
-Mathematical physics and stochastics
-Applied analysis
-Software engineering
-Theoretical computer science

The courses include group and lecture instruction, exercises, literature, and workshops. Most courses also include exams or project assignments. In addition, you can complete some courses independently, by taking exams.

Selection of the Major

This Master’s programme does not have any sub-programmes; instead, can can tailor a suitable combination according to your plans and existing knowledge from the modules in physics, mathematics, chemistry, and computer science. Your personal study plan will ensure that your courses will form a functional combination.

Programme Structure

The Master’s programme comprises 120 credits (ECTS) and it is possible to complete the degree in two academic years. The degree includes:
-90 credits of courses in the Master’s programme, including the Master’s thesis (Pro gradu) of 30 credits.
-30 credits of other courses from your Master’s programme or other programmes.

Your studies will include a personal study plan, working-life orientation, and career planning. The other studies could also include a traineeship, complementary courses in your major or minor subject, or a completely new minor subject.

Career Prospects

The Master’s degree in sciences applying theoretical and computational methods gives you an excellent basis for postgraduate studies or for work in many careers in Finland or internationally. Masters of Science employed within research and R&D in industry are very well paid. On the other hand, a career at the university or a research institute lets you carry out academic research on a topic of your own choosing.

As a graduate with an MSc degree you could embark on a career in:
-Industry, especially advanced technology corporations (applied research and R&D, leadership).
-Universities and research institutes abroad and in Finland (basic scientific research).
-Teaching in universities and universities of applied sciences.
-Software engineering, e.g. gaming industry.
-Various design and consultation jobs in the public and private sectors.

Graduates of similar programmes in the earlier degree system have found employment as researchers and teachers in universities and research institutes in Finland and abroad (e.g. CERN, ESA, NASA), for example, in administration (e.g. the Finnish Academy), and in private corporations. The strong analytical skills provided by the education are sought after in areas such as data analysis (industries, media companies, gaming industry, finance), and corporate research, product development, and consultation (e.g. Nokia, Ericsson, Apple, Sanoma, Spinverse, Supercell, Nielsen, Valo Research and Trading, Planmeca, Reaktor, Comptel, Vaisala, KaVo Kerr Group, IndoorAtlas and Goldman Sachs).

Internationalization

The Master’s programme works in a very international atmosphere, with many top researchers from Finland and abroad teaching in it. If you write your MSc thesis in one of the research groups, you will get first-hand experience of work in an international research project. In addition, the University of Helsinki and the Faculty of Science offer you many opportunities for international activities:
-Student exchange in one of the exchange locations of the faculty or university.
-Traineeships abroad.
-Courses given in English within the faculty.
-Cooperation with students in the international programme.
-International tasks within the students’ organisations or union.
-Language courses at the Language Centre of the University of Helsinki.

The Faculty of Science aims to be at the cutting edge of European research within its disciplines.

The collaboration partners include several top international research centres, such as CERN, ESA, ESRF, and ITER.R.

As a graduate student at the Faculty of Science, you will be able to apply for research training at places such as CERN in Geneva, Switzerland, or the ESRF centre in Grenoble, France. A traineeship in one of the internationally active research groups on campus will enable you to acquaint yourself and form contacts with the international research community during your studies. In addition, the international exchange programmes offer many opportunities for you to complete part of your degree at a foreign university.

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