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The University of Edinburgh, a prestigious institution in the United Kingdom, offers a ...
MSc Computational Applied Mathematics
The Kings Buildings Campus
INTAKE: September
Program Overview
The MSc in Computational Applied Mathematics is designed for students who want to develop a deep understanding of mathematical techniques and their practical applications in solving complex, real-world problems. The program offers a strong foundation in applied mathematics, numerical methods, and computational techniques, with an emphasis on developing the analytical and computational skills necessary to address challenges in science, engineering, and industry. Students will learn to apply advanced mathematical concepts to model real-world systems and use computational tools to analyze and solve problems effectively. The program is suitable for individuals aiming for careers in research, industry, or academia, particularly in areas such as data science, computational physics, finance, and engineering.
Curriculum: The curriculum for the MSc in Computational Applied Mathematics combines a blend of core and elective modules that cover a wide range of mathematical and computational concepts. Core modules typically include Advanced Computational Methods, Mathematical Modelling, Numerical Analysis, and Optimization Techniques. These courses introduce students to essential mathematical tools and computational methods used to solve large-scale, complex problems. Elective modules offer opportunities for specialization in areas such as Machine Learning, Computational Fluid Dynamics, Stochastic Processes, and Data Analysis. In addition to the coursework, students are required to complete a dissertation, where they can conduct independent research, applying their mathematical and computational skills to a topic of their choice. This research project allows students to explore a specific area of interest in greater depth and demonstrate their ability to solve complex problems.
Research Focus: The MSc in Computational Applied Mathematics is supported by the university’s vibrant research environment, which includes collaborations with other departments, research centers, and industry partners. Research at the University of Edinburgh spans a variety of areas, including mathematical modeling, numerical simulation, computational fluid dynamics, and machine learning. The university is known for its pioneering work in applied mathematics and computational science, with researchers using mathematical tools to model complex systems in areas such as engineering, finance, healthcare, and environmental science. Students in the program have the opportunity to engage with these cutting-edge research projects, applying their knowledge to real-world problems and contributing to ongoing academic advancements in applied mathematics.
Industry Engagement: The MSc in Computational Applied Mathematics benefits from the University of Edinburgh’s strong connections with various industries, including finance, engineering, data science, and technology. The university’s collaborations with industry partners ensure that students gain practical experience and exposure to real-world challenges. Throughout the program, students have opportunities to work on industry-related projects, attend seminars and workshops led by professionals, and participate in internships that provide hands-on experience in applying mathematical and computational techniques to solve practical problems. The program’s strong ties with industry help students develop the skills and networks necessary to secure roles in research and development, finance, technology, and other sectors that rely on computational mathematics.
Global Perspective: The MSc in Computational Applied Mathematics at the University of Edinburgh offers a global perspective by encouraging students to engage with mathematical and computational problems that have applications worldwide. The university attracts students from across the globe, creating a diverse and intellectually stimulating environment that promotes cross-cultural collaboration. The program emphasizes the importance of solving global challenges, such as climate change, healthcare, and technological innovation, using computational methods. Students are exposed to international best practices in applied mathematics and computational science, preparing them for careers that require a global outlook and the ability to address complex, large-scale problems across different industries.
Location
The Kings Buildings Campus
Score
IELTS: 6.5
Tuition Fee
£ 29900
Postgraduate entry requirements:
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Academic Qualifications: Prospective postgraduate applicants to the University of Edinburgh are typically required to have achieved a minimum academic qualification of approximately 60%, based on their previous academic achievements and qualifications.
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English Language Proficiency:
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IELTS (International English Language Testing System): Minimum overall score of 6.5, with at least 6.0 in each component (Listening, Reading, Speaking, Writing).
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TOEFL (Test of English as a Foreign Language): Minimum score of 100 on the internet-based test (iBT), with at least 20 in each component (Reading, Listening, Speaking, Writing).
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PTE (Pearson Test of English): Minimum overall score of 70, with at least 59 in each component (Listening, Reading, Speaking, Writing).
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Students must provide:
- academic marksheets & transcripts
- letters of recommendation
- a personal statement - SOP
- passport
- other supporting documents as required by the university.
Work experience: Some postgraduate courses may require relevant work experience in the field.
It is important to note that meeting the minimum entry requirements does not guarantee admission, as the university considers factors such as availability of places and competition for the program. Additionally, some courses may have higher entry requirements or additional selection criteria, such as interviews or portfolio submissions.
The University of Edinburgh offers a range of scholarships and funding opportunities specifically designed to support international students pursuing undergraduate, postgraduate, and research programs. These scholarships aim to promote diversity, academic excellence, and global engagement.
Global Scholarships: The University of Edinburgh offers Global Scholarships to outstanding international undergraduate students. These scholarships provide financial assistance towards tuition fees and living expenses, enabling talented students from around the world to access quality education at Edinburgh.
Edinburgh Global Research Scholarships: International postgraduate students pursuing research-based programs (Ph.D., MSc by Research) can apply for Edinburgh Global Research Scholarships. These scholarships provide full or partial funding for tuition fees and living expenses during the research program.
School-specific Scholarships: Some academic schools and departments within the university offer scholarships targeting international students in specific disciplines or programs. These scholarships may be merit-based or need-based and vary in terms of eligibility criteria and funding amounts.
Commonwealth Scholarships: The University of Edinburgh participates in various Commonwealth scholarship schemes, providing opportunities for students from Commonwealth countries to study in the UK. These scholarships are funded by the UK government and other organizations.
External Funding Sources: International students are encouraged to explore external funding sources, such as government scholarships, private organizations, and international foundations, to support their studies at the University of Edinburgh.
It is important to note that scholarship availability, criteria, and application deadlines may change from year to year.
The MSc Computational Applied Mathematics equips graduates with versatile skills that are highly valued across industries. Career opportunities are diverse, ranging from academic research to applied roles in finance, technology, engineering, and beyond. The program's strong emphasis on computational techniques ensures that graduates are well-prepared for the demands of a data-driven and analytically focused job market.
Research and Academia: Graduates of the MSc Computational Applied Mathematics program are well-prepared to pursue further academic studies, including PhD research in applied mathematics, computational science, or related fields. They may secure positions as research assistants or academic staff in universities and research institutions, contributing to the advancement of mathematical sciences.
Financial Services: The financial sector values graduates with strong quantitative skills. Computational applied mathematicians find opportunities in investment banking, asset management, and risk analysis roles. They contribute to algorithmic trading, quantitative modeling, and development of financial products.
Technology and Data Science: With expertise in numerical methods and computational modeling, graduates can pursue careers in technology companies and startups. Roles in data analysis, machine learning, and software development benefit from a solid foundation in applied mathematics.
Engineering and Industry: Various industries, such as aerospace, automotive, energy, and manufacturing, require mathematical modeling for design, optimization, and simulation. Graduates can work as mathematical analysts, simulation engineers, or research scientists in these sectors.
Consulting and Analytics: Consulting firms and analytics companies recruit graduates with computational and analytical skills to solve complex business problems. Careers in management consulting, operations research, and business analytics are viable options.
Government and Policy Analysis: Public sector roles involve analyzing data and developing models to inform policy decisions. Graduates may work in government agencies, research institutes, or international organizations focused on areas like healthcare, environment, or urban planning.
Entrepreneurship: Some graduates choose to start their own businesses, leveraging their mathematical expertise to develop innovative solutions or consultancy services in specialized areas such as data science or computational finance.
