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Masters degrees in Stochastic Processes focus on systems and processes involving random variables.
Related subjects include Financial Mathematics, Scientific Computation and Applied Stochastics. Entry requirements typically include an appropriate undergraduate degree in a relevant mathematical discipline.
Stochastics can be used to efficiently describe the randomness in all systems present in the natural and social world. As such, stochastic processes can help explain data collected about these systems, an ability that is useful across several industries.
For example, you might specialise in statistical mechanics, applying probability theory to study the behaviour of a mechanical system when its functional state is uncertain. This expertise can be applied to industries such as aerospace engineering and automotive design, as well as manufacturing.
Alternatively, you may work within financial markets such as insurance, investments and banking, analysing the stock exchange, predicting potential losses and optimising profits. Similarly, you may be involved in operational research for a variety of organisations, modelling budgets and other activities.
If a career in academia is of interest to you, your Masters would provide ideal groundwork for further study at PhD Level.
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The MRes in Stochastic Processes is delivered through optional modules for the taught course, followed by a substantial research project that explicitly contributes to the field, rather than applies existing knowledge. Read more
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Sussex has a prestigious international reputation and is ranked amongst the top 20 universities in the UK, with both departments ranked amongst the top 15 (Guardian University Guide 2018).