Scientific Computing and Data Analysis: AI Infrastructure Platforms MSc

Durham University

Developments in fields such as robotics, physics, engineering, earth sciences or finance are increasingly driven by experts in computational techniques. Those with the skills to write code for the most powerful computers in the world and to process the biggest data sets in the world can truly make a difference.Our suite of Masters in Scientific Computing and Data Analysis (MISCADA) offers an application-focused course to deliver these skills with three interwoven strands:Computer Science underpinnings of scientific computing (algorithms, data structures, implementation techniques, and computer tool usage)Mathematical aspects of data analysis and the simulation and analysis of mathematical modelsImplementation and application of fundamental techniques in an area of specialisation (as well as Computer Vision and Robotics, we offer options in Astrophysics, Engineering, AI Platforms, Financial Technology, or Environmental and Geographic Information Systems).There’s great synergy between the modules, and you will be given plenty of opportunities to put your learning into practice from the start of the course. Our research-led approach allows you to take some of the newest theoretical ideas and directly translate them into working codes in their respective application areas. If you have an undergraduate degree in a science subject with a strong quantitative element, including computer science and mathematics and want to work at the highest level in high-performance computing, either in academia or in industry, then this could be the course you’re looking for.