400-004-8861
The MSc in Scientific Computing and Data Analysis 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; Implementation and application of fundamental techniques in a domain specialisation (presently astrophysics, particle physics, or financial mathematics). The course is structured into five modules spanning three terms and is currently available with a specialisation in astrophysics, particle physics, or financial mathematics. Schematic timetable Term 1 Term 2 Term 3 Professional Skills (15 credits) Software carpentry Agile Software Project Management Systematic Testing and Reproducibility Version Control and Continuous Integration Presentation and Ethics Technical & Scientific Report Writing Ethics of Data Science Communicating Science Entrepreneurial Thinking Innovation management Change management Computational intelligence Core Modules Core I modules (30 credits) Core II modules (30 or 45 credits; depends on the weight of the specialisation – sum of all modules has to be 180) Please consult List A from the core regulations. Project Duration: 8-10 weeks Written thesis Options with external partner, typically in a team of 2-3 students; within subject specialisation; or with methodological work. (60 credits) Subject specialisation (30 or 45 credits) Please consult list B from the core regulations.