• Birmingham City University Featured Masters Courses
  • Northumbria University Featured Masters Courses
  • University of Derby Online Learning Featured Masters Courses
  • University of Bristol Featured Masters Courses
  • Xi’an Jiaotong-Liverpool University Featured Masters Courses
  • University of Surrey Featured Masters Courses
  • Ulster University Featured Masters Courses
Nottingham Trent University Featured Masters Courses
Cranfield University Featured Masters Courses
Buckinghamshire New University Featured Masters Courses
University College London Featured Masters Courses
FindA University Ltd Featured Masters Courses
"numerical" AND "methods"…×
0 miles

Masters Degrees (Numerical Methods)

We have 234 Masters Degrees (Numerical Methods)

  • "numerical" AND "methods" ×
  • clear all
Showing 1 to 15 of 234
Order by 
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.

About this degree

This programme aims to provide a rigorous formal training in computational science 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 Computing

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.

Further information on modules and degree structure is available on the department website: Scientific Computing MSc

Funding

For a comprehensive list of the funding opportunities available at UCL, including funding relevant to your nationality, please visit the Scholarships and Funding website.

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 enables 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 7th in QS World University Rankings 2018). Furthermore, the Thomson Scientific Citation Index shows that UCL is the second-most highly cited European university and 12th 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 enables students to tackle real-life problems in a structured and rigorous way and produce professional software for their efficient solution.



Read less
The course provides you with a strong mathematical background with the skills necessary to apply your expertise to the solution of real finance problems. … Read more

The course provides you with a strong mathematical background with the skills necessary to apply your expertise to the solution of real finance problems. You will develop skills so that you are able to formulate a well posed problem from a description in financial language, carry out relevant mathematical analysis, develop and implement an appropriate numerical scheme and present and interpret these results.

The course lays the foundation for further research in academia or for a career as a quantitative analyst in a financial or other institution.

You will take three introductory courses in the first week. The introductory courses cover partial differential equations, probability and statistics and MATLAB.

The first term focuses on compulsory core material, offering 80 hours of lectures and 40 hours of classes/practical. The core courses are as follows:

  • Stochastic Calculus
  • Financial Derivatives
  • Numerical Methods I - Monte-Carlo
  • Numerical Methods I - Finite Differences
  • Statistics and Financial Data Analysis
  • Financial Programming with C++ 1

In the second term, three streams are offered; each stream consists of 32 hours of lectures and 16 hours of classes/practical. The Tools stream is mandatory and you will also take either the Modelling stream or the Data-driven stream.

Modelling stream

  • Exotic derivatives
  • Stochastic volatility, jump diffusions
  • Commodities
  • Fixed income

Data-driven stream

  • Asset pricing and inefficiency of markets
  • Market microstructure and trading
  • Algorithmic trading
  • Advanced financial data analysis
  • Machine learning
  • Python

Tools stream

  • Numerical methods 2 - Monte Carlo methods
  • Numerical methods 2 - Finite differences
  • Calibration
  • Optimisation
  • Introduction to stochastic control

As well as the streams, the course includes a compulsory one-week (24 hours of lectures) intensive module on quantitative risk management which is to be held in/around the week before the third term.

The third term is dedicated to a dissertation project which is to be written on a topic chosen in consultation with your supervisor.

The second component of the financial computing course, Financial Computing with C++ 2 (24 hours of lectures and practicals in total), is held shortly after the third term.

The examination will consist of the following elements:

  • two written examinations and one take-home project, each of two hours' duration - the written examinations will cover the core courses in mathematical methods and numerical analysis
  • a written examination on the Modelling stream or a written examination and a computer-based practical examination on the Data-driven stream
  • a written examination assessing the Tools stream
  • a take-home project assessing the course in quantitative risk management
  • two practical examinations assessing two courses in financial computing with C++.

Graduate destinations

MSc graduates have been recruited by prominent investment banks and hedge funds. Many past students have also progressed to PhD-level studies at leading universities in Europe and elsewhere.



Read less
The Theoretical Physics track introduces the student to the intriguing diversity of physical theories and gives means to understand the world. Read more

The Theoretical Physics track introduces the student to the intriguing diversity of physical theories and gives means to understand the world. Topics from quantum physics to the theories of gravity are incorporated into the track. Problems of fundamental quantum physics, quantum information, quantum field theory and theoretical cosmology are at the heart of the studies in Theoretical Physics.

Upon graduation, you will be able to use the diverse set of skills acquired as part of this track, including theoretical and numerical techniques to produce and analyse new physical projects.

Programme structure 

The structure is modular. All modules have 20 ECTS. Each specialisation track has two obligatory modules that contain the core material of the field. In addition, there is one thematic module that may be chosen from the other modules offered within this programme or other programmes at the University of Turku. The fourth module consists of freely chosen courses and an obligatory Finnish language and culture course (5 ECTS). An MSc thesis (30 ECTS) in addition to seminar, internship, and project work (10 ECTS) are also required, details of which depend on the specialisation.

Academic excellence and experience

The aim of the Master’s education is to support you to become an independent expert who can evaluate information critically, plan and execute research projects to find new knowledge, and to solve scientific and technological problems independently and as a part of a group.

In the University of Turku the research in Theoretical physics has the emphasis on various fields at the forefront of European and international research such as quantum technologies, fundamentals of quantum physics, quantum information and optics, quantum field theory and cosmology. You will learn rigorous mathematical and numerical methods to model physical phenomena and solve physical problems with several possible interdisciplinary applications also outside physics. Examples are the studies of complex systems, data science, and machine learning.

Master's thesis and topics

The Master’s degree programme includes a compulsory thesis component (30 ECTS), which corresponds to six months of full time work. The thesis is to be written up as a report based on a combination of a literature review and an original research project that forms the bulk of the thesis.

The thesis is an independently made research project but the project will be carried out under the guidance of leading researchers in the field at the University of Turku. It is expected that the student will be embedded within an active research group or experimental team, thereby providing ample opportunity to discuss results and exchange ideas in a group setting.

Specialisation tracks

The Master’s Degree Programme of Physical and Chemical Sciences has four tracks. A short description of each specialisation track is given below. You can find more detailed information of tracks from the specific site of each track in this portal (UTU Masters).

In Theoretical physics you can specialise in various fields at the forefront of European and international research such as quantum technologies, fundamentals of quantum physics, quantum information and optics, quantum field theory and cosmology. You will learn rigorous mathematical and numerical methods to model physical phenomena and solve physical problems with several possible interdisciplinary applications also outside physics. Examples are the studies of complex systems, data science, and machine learning.

Students specialising in Astronomy and Space Physics can choose among three lines of studies: theoretical astrophysics, observational astronomy and space physics. You will acquire knowledge of various astrophysical phenomena and plasma physics, from Solar system to neutron stars and onto galaxies and cosmology. You will also get hands-on experience with observational techniques, space instrumentation, numerical methods and analysis of large data sets.

The studies of Materials Physics and Materials Chemistry give you an ability to understand and to develop the properties of materials from molecules and nanoparticles via metals, magnetic and semiconducting compounds for pharmaceutical and biomaterial applications. After graduation, you will be familiar with the current methodologies, research equipment and modern numerical methods needed to model properties of materials used in research and technology. Note that there is a sister programme (Master’s Degree Programme in Biomedical Sciences) with a specialisation in medicinal chemistry.

Job options

The prospects for employment at relatively senior levels is excellent for those trained in the physical and chemical sciences. Thanks to the broad scope of the programme, the skills and knowledge developed as part of this education at the University of Turku provide many employment opportunities in different areas.

Our MSc graduates have been employed to wide range of professions, in addition to academic career, such that finance sector, medical imagining, quantum technology, game development, and data mining.

Career in research

The Master’s Degree provides eligibility for scientific postgraduate degree studies. Postgraduate degrees are doctoral and licentiate degrees. The University of Turku Graduate School – UTUGS has a Doctoral Programme in Physical and Chemical Sciences, and covers all of the disciplines of this Master Degree programme. Postgraduate degrees can be completed at the University of Turku. Note that in Finland the doctoral studies incur no tuition fees, and PhD students often receive either a salary, or a grant to cover their living expenses. The Master’s programme is a stepping stone for PhD studies.



Read less
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

Read less
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

Read less
The other tracks of the programme are Materials Chemistry, Materials Physics, and Theoretical Physics. Upon graduation, you will be able to use the diverse set of skills acquired as part of this track, including computational and numerical techniques. Read more

The other tracks of the programme are Materials Chemistry, Materials Physics, and Theoretical Physics. Upon graduation, you will be able to use the diverse set of skills acquired as part of this track, including computational and numerical techniques.

Programme structure 

The structure is modular. All modules have 20 ECTS. Each specialisation track has two obligatory modules that contain the core material of the field. In addition, there is one thematic module that may be chosen from the other modules offered within this programme or other programmes at the University of Turku. The fourth module consists of freely chosen courses and an obligatory Finnish language and culture course (5 ECTS). An MSc thesis (30 ECTS) in addition to seminar, internship, and project work (10 ECTS) are also required, details of which depend on the specialisation. 

Academic excellence and experience

The aim of the Master’s education is to support you to become an independent expert who can evaluate information critically, plan and execute research projects to find new knowledge, and to solve scientific and technological problems independently and as part of a group.

The Astronomy and Space Physics track includes a solid grounding in theoretical aspects as well as providing opportunities for observational studies (e.g. of supernovae or accreting black holes); the space physics group performs experimental, theoretical and computational research on high-energy phenomena in near-Earth space.

Master's thesis and topics

The Master’s degree programme includes a compulsory thesis component (30 ECTS), which corresponds to six months of full time work. The thesis is to be written up as a report based on a combination of a literature review and an original research project that forms the bulk of the thesis.

The thesis is an independently made research project but the project will be carried out under the guidance of leading researchers in the field at the University of Turku. It is expected that the student will be embedded within an active research group or experimental team, thereby providing ample opportunity to discuss results and exchange ideas in a group setting.

Specialisation tracks

The Master’s Degree Programme of Physical and Chemical Sciences has four tracks. A short description of each specialisation track is given below. You can find more detailed information of tracks from the specific site of each track in this portal (UTU Masters).

Students specialising in Astronomy and Space Physics can choose among three lines of studies: theoretical astrophysics, observational astronomy and space physics. You will acquire knowledge of various astrophysical phenomena and plasma physics, from Solar system to neutron stars and onto galaxies and cosmology. You will also get hands-on experience with observational techniques, space instrumentation, numerical methods and analysis of large data sets.

The studies of Materials Physics and Materials Chemistry give you an ability to understand and to develop the properties of materials from molecules and nanoparticles via metals, magnetic and semiconducting compounds for pharmaceutical and biomaterial applications. After graduation, you will be familiar with the current methodologies, research equipment and modern numerical methods needed to model properties of materials used in research and technology. Note that there is a sister programme (Master’s Degree Programme in Biomedical Sciences) with a specialisation in medicinal chemistry.

In Theoretical physics you can specialise in various fields at the forefront of European and international research such as quantum technologies, fundamentals of quantum physics, quantum information and optics, quantum field theory and cosmology. You will learn rigorous mathematical and numerical methods to model physical phenomena and solve physical problems with several possible interdisciplinary applications also outside physics. Examples are the studies of complex systems, data science, and machine learning.

Competence description

The Master of Science degree provides the skills to work in many different kinds of positions within areas such as research and development, education and management, and industry. The specialisations of Astronomy and Space Physics provide very good data analysis and programming skills, and thus many graduates have gone on to successful careers in the big data and finance sectors

During the master’s program in astronomy and space physics, you will study plasma physics and hydrodynamics, radiative processes, high-energy astrophysics and solar physics, galaxies and cosmology, astrophysical spectroscopy, radio astronomy and X-ray and gamma-ray astronomy, numerical techniques and programming, statistical methods and particle and photons detectors. You will carry-out hands-on exercises in observational techniques, space instrumentation, and analysis of large data sets. You will also be able to remotely use modern observational facilities and to participate in building space-qualified instruments. You may choose among three lines: space physics, observational astrophysics and theoretical astrophysics. These studies will prepare you for a career in research and development in industry or can often lead into PhD studies.

Job options

The prospects for employment at relatively senior levels is excellent for those trained in the physical and chemical sciences. Thanks to the broad scope of the programme, the skills and knowledge developed as part of this education at the University of Turku provide many employment opportunities in different areas.

Many of our graduates choose to continue their education by pursuing PhD studies in Finland or other European countries (e.g., Belgium, Estonia, Germany and Norway). Others have obtained employment in the software and high-tech industries, for example.

Career in research

The Master’s Degree provides eligibility for scientific postgraduate degree studies. Postgraduate degrees are doctoral and licentiate degrees. The University of Turku Graduate School – UTUGS has a Doctoral Programme in Physical and Chemical Sciences, and covers all of the disciplines of this Master Degree programme. Postgraduate degrees can be completed at the University of Turku. Note that in Finland the doctoral studies incur no tuition fees, and PhD students often receive either a salary, or a grant to cover their living expenses. The Master’s programme is a stepping stone for PhD studies.



Read less
Materials Physics is one of the four specialisation tracks of the Master’s Degree Programme in Physical and Chemical Sciences. Read more

Materials Physics is one of the four specialisation tracks of the Master’s Degree Programme in Physical and Chemical Sciences. The other tracks of the programme are Astronomy and Space Physics, Materials Chemistry, and Theoretical Physics. Upon graduation, you will be able to use the diverse set of skills acquired as part of this track, including experimental, theoretical and numerical techniques to produce and analyse new physical projects.

Programme structure 

The structure is modular. All modules have 20 ECTS. Each specialisation track has two obligatory modules that contain the core material of the field. In addition, there is one thematic module that may be chosen from the other modules offered within this programme or other programmes at the University of Turku. The fourth module consists of freely chosen courses and an obligatory Finnish language and culture course (5 ECTS). An MSc thesis (30 ECTS) in addition to seminar, internship, and project work (10 ECTS) are also required, details of which depend on the specialisation. 

Academic excellence and experience

The aim of the Master’s education is to support you to become an independent expert who can evaluate information critically, plan and execute research projects to find new knowledge, and to solve scientific and technological problems independently and as part of a group.

In the University of Turku, the research and teaching of materials physics has as two focal areas bio- and electronic materials. In biomaterials, you can study e.g. pharmaceutical vectors, nanoporous materials in pharmaceutics and dissociation of DNA-molecules under radiation. In electronics materials, possible topics include semiconducting, magnetic and superconducting materials, spintronics and nanocontacts. You will study the physical basis of current and future electronics.

Master's thesis and topics

The Master’s degree programme includes a compulsory thesis component (30 ECTS), which corresponds to six months of full time work. The thesis is to be written up as a report based on a combination of a literature review and an original research project that forms the bulk of the thesis.

The thesis is an independently made research project but the project will be carried out under the guidance of leading researchers in the field at the University of Turku. It is expected that the student will be embedded within an active research group or experimental team, thereby providing ample opportunity to discuss results and exchange ideas in a group setting.

Recent examples of thesis titles in materials physics have been:

  • Self-organised artificial pinning structure in small-scale YBCO films grown on an advanced IBAD-MgO based template
  • Fabrication and characterisation of resistive memories based on Pr6Ca0.4MnO3
  • Photoluminescence of thermally carbonized and wet-oxidized porous silicon
  • Physical and chemical characterisation methods for metal powders used for additive manufacturing process
  • Surface properties of GaN- and AlGaN-semiconductors and their modification
  • Geometric corrections in computer tomography images
  • Mass spectroscopy investigation of fragmentation of uridine and cytidine molecules

Specialisation tracks

The Master’s Degree Programme of Physical and Chemical Sciences has four tracks. A short description of each specialisation is given below. You can find more detailed information of tracks from the specific site of each track in this portal (UTU Masters).

The studies of Materials Physics and Materials Chemistry give you an ability to understand and to develop the properties of materials from molecules and nanoparticles via metals, magnetic and semiconducting compounds for pharmaceutical and biomaterial applications. After graduation, you will be familiar with the current methodologies, research equipment and modern numerical methods needed to model properties of materials used in research and technology. Note that there is a sister programme (Master’s Degree Programme in Biomedical Sciences) with a specialisation in medicinal chemistry.

Students specialising in Astronomy and Space Physics can choose among three lines of studies: theoretical astrophysics, observational astronomy and space physics. You will acquire knowledge of various astrophysical phenomena and plasma physics, from Solar system to neutron stars and onto galaxies and cosmology. You will also get hands-on experience with observational techniques, space instrumentation, numerical methods and analysis of large data sets.

In Theoretical physics you can specialise in various fields at the forefront of European and international research such as quantum technologies, fundamentals of quantum physics, quantum information and optics, quantum field theory and cosmology. You will learn rigorous mathematical and numerical methods to model physical phenomena and solve physical problems with several possible interdisciplinary applications also outside physics. Examples are the studies of complex systems, data science, and machine learning.

Job options

The prospects for employment at relatively senior levels is excellent for those trained in the physical and chemical sciences. Thanks to the broad scope of the programme, the skills and knowledge developed as part of this education at the University of Turku provide many employment opportunities in different areas.

Our recent MSc’s work e.g. as quality managers in large companies, R&D engineers in biotech and materials companies, security engineers at nuclear power plants.

Career in research

The Master’s Degree provides eligibility for scientific postgraduate degree studies. Postgraduate degrees are doctoral and licentiate degrees. The University of Turku Graduate School – UTUGS has a Doctoral Programme in Physical and Chemical Sciences, and covers all of the disciplines of this Master Degree programme. Postgraduate degrees can be completed at the University of Turku. Note that in Finland the doctoral studies incur no tuition fees, and PhD students often receive either a salary, or a grant to cover their living expenses. The Master’s programme is a stepping stone for PhD studies.



Read less
This one-year programme at the University of Edinburgh will immerse you in the most current developments in chemical engineering, through a combination of taught modules, workshops, a research dissertation, and a number of supporting activities delivered by the key experts in the field. Read more

This one-year programme at the University of Edinburgh will immerse you in the most current developments in chemical engineering, through a combination of taught modules, workshops, a research dissertation, and a number of supporting activities delivered by the key experts in the field.

The programme will develop from fundamental topics, including modern approaches to understanding properties of the systems on a molecular scale and advanced numerical methods, to the actual processes, with a particular emphasis on energy efficiency, to the summer dissertation projects where the acquired skills in various areas are put into practice, in application to actual chemical engineering problems.

Programme structure

The programme develops from compulsory courses, emphasizing modern computational techniques and research methods, to a range of options. It is complemented by a strong management and economics component, culminating in a research project leading to a masters thesis.

Compulsory Courses

  • Numerical Methods for Chemical Engineers
  • Molecular Thermodynamics
  • Introduction to Research Methods

Optional Courses

Students must select one of the following courses during semester one:

  • Chemical Reaction Engineering
  • Fire Science and Fire Dynamics
  • Process Safety
  • Computational Fluid Dynamics
  • Group Design Project (Power Station with Carbon Capture and Storage)

Plus, five or six courses (depending on the weighting of the course) from the options listed below in semester two:

  • Adsorption
  • Separation Processes
  • Membrane Separation Processes
  • Batchwise and Semibatch Processing
  • Oil and Gas Systems Engineering
  • Polymer Science and Engineering
  • Supply Chain Management
  • Modern Economic Issues in Industry
  • Technology and Innovation Management
  • Nanotechnology
  • Engineering in Medicine
  • Nanomaterials in Chemical and Biomedical Engineering

Learning outcomes

  • A working knowledge of modern modelling and simulation approaches to understanding properties of chemical systems at a molecular level.
  • A working knowledge of advanced experimental techniques, such as for example particle image velocimetry, spectroscopy and infra-red thermography, as applied in engineering research and development.
  • Ability to transform a chemical engineering problem into a mathematical representation; broad understanding of the available numerical tools and methods to solve the problem; appreciation of their scope and limitations.
  • An understanding of the basic design approaches to advanced energy efficient separation processes.
  • Ability to transfer and operate engineering principles in application to other fields, such as biology.
  • Proficiency in using modern chemical engineering software, from molecular visualisation to computational fluid dynamics to process engineering.

On completion of the research dissertation, the students will be able to:

  • Plan and execute a significant research project
  • Apply a range of standard and specialised research instruments and techniques of enquiry
  • Identify, conceptualise and define new and abstract problems and issues
  • Develop original and creative responses to problems and issues
  • Critically review, consolidate and extend knowledge, skills practices and thinking in chemical engineering
  • Communicate their research findings, using appropriate methods, to a range of audiences with different levels of knowledge and expertise
  • Place their research in the context of the current societal needs and industrial practice
  • Adhere to rigorous research ethics rules
  • Exercise substantial autonomy and initiative in research activities
  • Take responsibility for independent work
  • Communicate with the public, peers, more senior colleagues and specialists
  • Use a wide range of software to support and present research plans and findings

Career opportunities

Our graduates enjoy diverse career opportunities in oil and gas, pharmaceutical, food and drink, consumer products, banking and consulting industries. Examples of the recent employers of our graduates include BP, P&G, Mondelēz International, Doosan Babcock, Atkins, Safetec, Xodus Group, Diageo, Wood Group, GSK, Gilead Sciences, ExxonMobil, Jacobs, Halliburton, Cavendish Nuclear to name a few. This wide range of potential employers means that our graduates are exceptionally well placed to find rewarding and lucrative careers. According to the Complete University Guide, the chemical engineering programme at the University of Edinburgh is ranked one of the top in the UK in terms of graduates prospects.

Find out more about career opportunities:

The MSc in Advanced Chemical Engineering may also lead to further studies in a PhD programme. With the 94% of our research activity rated as world leading or internationally excellent (according to the most recent Research Excellence Framework 2014), Edinburgh is the UK powerhouse in Engineering. As an MSc student at Edinburgh you will be immersed in a research intensive, multidisciplinary environment and you will have plenty of opportunities to interact with PhD, MSc students and staff from other programmes, institutes and schools.

Find out more about our research:



Read less
The MSc in Computational Finance will introduce students to the computational methods that are widely used by practitioners and financial institutions in today's markets. Read more

The MSc in Computational Finance will introduce students to the computational methods that are widely used by practitioners and financial institutions in today's markets. This will provide students with a solid foundation not only in traditional quantitative methods and financial instruments, but also scientific computing, numerical methods, high-performance computing, distributed ledgers, big-data analytics, and agent-based modelling. These techniques will be used to understand financial markets from a post-crisis perspective which incorporates findings from the study of financial markets at high-frequency time scales, modern approaches to understanding systematic risk and financial contagion, and disruptive technologies such as distributed-ledgers and crypto-currencies. The programme is highly practical, and students will have the opportunity to apply their learning to real-world data and case studies in hands-on laboratory sessions.

Key benefits

  • An understanding of modern financial technology (FinTech) including electronic trading and distributed-ledger technology.
  • Practical hands-on techniques for working with and analysing financial data, which draw on modern developments in Artificial Intelligence and Big Data technology.
  • The opportunity to understand the practical aspects of quantitative finance and FinTech from Industry experts located in the heart of one of the World’s financial centres.

Description

Computational Finance studies problems of optimal investment, risk management and trade execution from a computational perspective. As with any engineering discipline, computational finance analyses a given problem by first building a model for it and then examining the model. In computational finance, however, our model is typically analysed by running computer programs, rather than solving mathematical equations. In addition to standard computational methods such as Monte-Carlo option pricing, you will also learn more advanced modelling techniques such as agent-based modelling, in which the model itself takes the form of a computer program.

The programme will provide a foundation in the core skills required for successful risk management and optimal investment by giving a grounding in the key quantitative methods used in finance, including computer programming, numerical methods, scientific computing, numerical optimisation, and an overview of the financial markets. You can then go on to study more advanced topics, including the market micro-structure of modern electronic exchanges, high-frequency finance, distributed-ledger technology and agent-based modelling.

Career prospects

Students are expected to go in to careers such as Investment Banking, Hedge Funds and Regulatory Bodies.  

Sign up for more information. Email now

Have a question about applying to King’s? Email now



Read less
Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Erasmus Mundus Computational Mechanics at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017). Read more

Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Erasmus Mundus Computational Mechanics at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017).

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



Read less
The ICMA Centre’s financial engineering degree is highly respected by quantitative analysts and their employers. The credit crunch and subsequent events have emphasised the need to develop better pricing and better hedging models for all complex products. Read more

The ICMA Centre’s financial engineering degree is highly respected by quantitative analysts and their employers. The credit crunch and subsequent events have emphasised the need to develop better pricing and better hedging models for all complex products. The practical and quantitative skills that you will develop on the programme will equip you to meet this challenge.

Our compulsory modules provide a firm grounding in probability theory, stochastic calculus, derivatives pricing, quantitative and numerical methods, structuring products, volatility analysis, and the modelling of credit, equity, foreign exchange and interest rate derivatives. We also provide a thorough training in C++ and other programming tools.

Optional modules will allow you to focus on risk analysis, portfolio management, designing trading strategies or econometric analysis. This newly structured degree aims to further enhance the strong reputation of its precursor – the MSc in Financial Engineering and Quantitative Analysis, which was established back in 1999. A good background in mathematics is required for acceptance to this programme (see entry requirements below).

Highlights

  • A highly technical programme for those with strong mathematical skills
  • Gain knowledge of derivatives pricing tools and methods, as well as the use of programming languages like C++ and VBA
  • Designed with the support of industry practitioners to equip students with the skills and knowledge needed to succeed
  • Graduates are able to make an early contribution through the unique combination of hands-on, practical skills and the necessary underlying finance theory
  • Benefit from the combined expertise of both the ICMA Centre and the Department of Mathematics

Course structure

October – December: Part 1 Autumn Term

January: Part 1 Exams

January-April: Part 2 Spring Term

May – June: Part 2 Exams

June – August (12 month programme only): Part 3

August/Sep (12 month programme only): Part 3 Coursework deadlines

Course content

Part 1 compulsory modules

Part 2 compulsory modules

Part 2 optional modules

Students on the 9-month (12-month) programme can select 40 (20) credits from the following modules:

Part 3 optional modules

Optional modules

Students on the 12-months programme should take 20 credits from the following:

Learning options

Full-time: 9 months Full-time: 12 months

Students will be resident and undertake full-time study in the UK. Under both, the 9 and 12-month programmes students take compulsory and/or elective modules in Part 2.

The 12 month option involves taking an elective 20 credit module between July and August, which would also mean a 20 credit reduction in the number of taught modules taken in the spring term.

Careers

Many of our financial engineering graduates are now working as Quants in large London banks and other financial institutions. Others have pursued PhDs and have successful academic careers. Financial instruments are becoming ever more sophisticated, so graduates that understand complex modelling techniques are always in great demand. The high quantitative content of this programme opens many doors to a wide range of careers. You could structure and develop new debt or equity solutions to meet clients funding and hedging needs, or you could become a proprietary trader in exotic derivatives, or a software specialist or a quantitative analyst supporting the traders.

There are excellent opportunities on the buy-side, with hedge funds and investment institutions, as well as in investment banking and in software analytics. Opportunities in quantitative research, or with a rating agency, are among the many other attractive alternatives. Outside of mainstream banking and investment, you might also consider firms involved in commodity and energy trading, or the treasury divisions of leading multinationals and management consultancies.

Professional accreditation

ICMA Fixed Income Certificate

To obtain the requisite knowledge to pass the rigorous FIC exam, students are required to take the ICMA Centre Fixed Income Cash and Derivatives Markets module at Part 2. In order to receive the FIC certificate, students will need to register and pass the FIC exam through ICMA.



Read less
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.



Read less
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. 

Read less
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.

Read less
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/

Read less

Show 10 15 30 per page



Cookie Policy    X