MSc Computational Applied Mathematics

The Kings Buildings Campus

 

INTAKE: September

Program Overview

The MSc in Computational Applied Mathematics at The University of Edinburgh offers an advanced study of mathematical methods and their application to real-world problems, emphasizing computational techniques and their implementation. This program equips students with the analytical skills and computational tools necessary to tackle complex mathematical challenges across various fields.The MSc Computational Applied Mathematics program at The University of Edinburgh is ideal for students seeking to deepen their knowledge of applied mathematics and gain proficiency in computational techniques. It prepares graduates for successful careers in fields where mathematical modeling and numerical analysis play a critical role in innovation and problem-solving.

  1. Advanced Mathematical Techniques: The program delves into advanced mathematical theory and techniques, providing students with a deep understanding of numerical methods, optimization, differential equations, and statistical analysis. These skills are essential for modeling and simulating complex systems encountered in scientific research and industrial applications.

  2. Computational Tools and Algorithms: Students gain expertise in programming languages, numerical algorithms, and computational software packages used to solve mathematical problems efficiently. They learn to implement and optimize algorithms, gaining hands-on experience in high-performance computing.

  3. Interdisciplinary Applications: Computational Applied Mathematics finds applications in diverse areas such as physics, engineering, finance, and biology. The program emphasizes interdisciplinary collaboration and encourages students to apply mathematical concepts to solve real-world problems in these domains.

  4. Research-Led Teaching: The curriculum is designed to reflect the latest developments in applied mathematics research. Students engage with cutting-edge topics and have the opportunity to undertake individual or group projects that explore emerging areas of computational mathematics.

  5. Career Preparation: Graduates of this program are well-equipped for careers in academia, research institutions, finance, technology, and engineering. They possess strong analytical and problem-solving skills, making them valuable assets in industries that rely on mathematical modeling and data analysis.

Pollster Education

Location

The Kings Buildings Campus

Pollster Education

Score

IELTS: 6.5

Pollster Education

Tuition Fee

£ 29900

Postgraduate entry requirements:

  1. 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.  

  2. English Language Proficiency:  

    • IELTS (International English Language Testing System): Minimum overall score of 6.5, with at least 6.0 in each component (Listening, Reading, Speaking, Writing).

    • 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).

    • PTE (Pearson Test of English): Minimum overall score of 70, with at least 59 in each component (Listening, Reading, Speaking, Writing).

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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.


Similar Courses
WhatsApp Enquiry Call Enquiry