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The Scientific Computing (SciComp) research group studies the generic methodological, algorithmic, and theoretical challenges that underpin computer simulations and the analysis of numerical data in research areas across science, engineering, and medicine.
Its members work on the whole range from numerical and statistical methods through algorithms, implementation techniques, software development tools to hardware aspects to develop new understanding in how to exploit high-performance computer architectures with unprecedented efficiency, how to write robust and fast simulation codes, how to fuse data with first-principle models, how to design mature, correct and sustainable scientific codes, how to distribute workload on massive computers, how to generate, process and distill high-dimensional, multifaceted data, and how to identify fundamental runtime, complexity and correctness properties behind simulation codes. To get a broader flavour of this, see recent publications from group members.
The group closely interacts with various computational and data-driven disciplines in Durham, contributes to large-scale, world-leading simulation software packages, actively engages with Durham’s and the UK’s supercomputing agenda, and leads the inter-departmental MSc in Scientific Computing and Data Analysis. Group members have access to excellent computational facilities and cutting edge hardware through ARC.