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Masters degrees in Mathematics explore advanced mathematical theory and numerical analysis together with their applications in a range of practical contexts from statistics to computing.
Some programmes in this discipline are taught courses, developing core mathematical competencies and advanced numeracy skills. Others are independent research degrees, focussing on theoretical or practical problem-solving techniques. Some are also highly disciplinary, with the opportunity to apply numerical reasoning to the challenges encountered in medical, engineering, or business contexts.
Courses commonly award MSc, MRes or MPhil degrees, depending on their specific areas of focus.
Though it may seem like the textbook example of an academic discipline (often involving very weighty textbooks!) Mathematics might surprise you at postgraduate level. Many courses are already highly vocational. You could train for a role in insurance and risk management, in financial trading or even in epidemiology (the process of measuring and predicting public health and disease trends).
Other programmes are more theoretical, but even a Masters in Pure Mathematics can have professional applications. Your skills in quantitative analysis and numerical reasoning will be second to none, equipping you to deal effectively with complex data and statistical problems in a wide range of working environments.
Of course, Mathematics is also a fertile academic research area, with connections to other disciplines including the Physical Sciences, Engineering and even Philosophy.
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Why does one car have more air resistance than another? How can the frequency of the electric power smart grid be kept constant under external disturbances? Applied Mathematics is concerned with the development and application of mathematical tools for the analysis and design of dynamical systems that appear in modern technology. Read more
How does a bank check whether your digital signature is a valid one? Do planets move in stable orbits or will they eventually collide? How can a 3D-sphere within the 3D-figures be characterised? The mathematics behind these questions is dealt within your Master's degree programme. Read more
Do you want to develop the mathematical skills sought out by so many employers? Do you want to follow your passion and pursue further study in mathematics? Are you considering a career in research within academia or industry? If so, this degree is for you. Read more
Understand the main aspects of quantitative finance – including general finance theory, finance models and programming for graduates with a science, engineering and mathematics background. Read more
The recent progress in several fields of theoretical physics (such as high energy physics, astrophysics, quantum and nonlinear optics or condensed matter physics) required numerous very sophisticated mathematical tools. Read more
On this course, you’ll. gain an understanding of the main aspects of risk management in business apply mathematics to financial risk description, analysis and quantification experience Sussex’s strong foundation of interdisciplinary research. Read more
We are surrounded by data. The variety and amount we collect and store grows every day, from the simplest of retail transactions to the complex and intimate medical records of millions. Read more
Our Applied MSc in Data Science & Artificial Intelligence programme, with its two entries in Autumn and Spring , will enable you to get a deep understanding of the main scientific grounds for artificial intelligence techniques, centred on modelling and then implementing rather than surveying data science APIs & frameworks. Read more
Do you wish to work in industry or plan to pursue further study? Are you interested in data science and its application to science and technology? If so, this course is for you. Read more
With the aim of developing solid technical, organizational, leadership, critical thinking and communication competencies for future, the Master’s in Business Analytics prepares future managers and leaders of organizations (public or private, for-profit or not-for-profit) in a context increasingly dependent on algorithms and hybrid (human-machine) systems for decision making. Read more