MSc in Scientific Computing and Data Analysis (Earth and Environmental Sciences), Durham University

Durham - UK,

12 Months

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About this course

This MSc program focuses on developing expertise in advanced scientific computing and data analysis techniques, specifically tailored to address critical issues related to Earth and environmental sciences. Students will learn to predict and analyze aspects of climate change, environmental risks, hazards, and natural resource exploitation using powerful datasets and sophisticated computational tools. Emphasizing application-driven learning, the course combines core modules in algorithms, high-performance computing, and data analysis with more specialized topics in Earth sciences, including geospatial data and societally-relevant problems. The program offers hands-on experience through practical analysis, field trips, and a substantial research project, ensuring students are well-equipped to translate theoretical knowledge into real-world environmental solutions.

Why this course is highly recommended

If you have a background in a science subject with a strong quantitative element and want to work at the highest levels in Earth and environmental sciences, this course offers a unique blend of cutting-edge computational techniques and environmental expertise. The program's research-led approach, practical training, and focus on societal relevance make it ideal for students aiming for careers in academia or industry, particularly in sectors related to climate change, resource management, and environmental protection.

Specialisation

The specialisation in Earth and Environmental Sciences is designed to equip students with advanced skills in handling diverse datasets, deploying mathematical and software tools for environmental analysis, and addressing pressing societal issues. This includes training in analyzing satellite data, geospatial information, and other environmental datasets, along with mathematical techniques for computational analysis. The course emphasizes applying these skills to real-world environmental challenges, combining theoretical learning with practical exercises, fieldwork, and a final research project.

Course fees

Application fees

1st year tuition fees

35.89L

Living cost

Degree requirements

Applicants need a UK first or upper second class honours degree (BSc) or equivalent in physics, computer science, mathematics, earth sciences, engineering, or natural sciences with a strong quantitative focus. Strong programming skills in at least one compiled language such as C or C++ are required, with proficiency in Python acceptable if complemented by a solid background. Knowledge of undergraduate mathematics (linear algebra, calculus, differential equations, probability) is also essential.

English language test

PTE

TOEFL

DUOLINGO

IELTS

6.5

Career prospects

Graduates from this program can look forward to careers across industry and academia. They are well-positioned for roles in software engineering, data analysis, environmental consultancy, climate modeling, and resource management. The course's industry links with sectors like automotive, defense, government, and high-tech companies ensure students have access to numerous employment opportunities in sectors such as technology, environmental policy, and scientific research.

FAQs

What are the main modules included in this course?

Core modules include Introduction to Machine Learning and Statistics, Scientific and High Performance Computing, Professional Skills, a substantial Project, and an Earth and Environmental Sciences module. Optional modules may include Advanced Statistical and Machine Learning, Data Acquisition, Performance Modelling, Algorithms, Linear Algebra, and more.

What are the English language requirements?

The input data mentions that the university's guidance on required English language levels applies, but specific scores or tests are not detailed here.