The Centre for Scientific Computing is a multidisciplinary research centre hosting internationally competitive research groups that employ high performance computing tools to achieve their research goals. This research is underpinned by graduate and advanced level teaching, and by stateof- the-art computing facilities. The Centre has a broad research base and is inherently multidisciplinary in its research agenda. The Centre currently encompasses more than 20 academic staff and their research groups from most of the Natural Sciences at Warwick.
The CSC established itself as one of two national EPSRC-funded training centres in high-end computing and now leads the national consortium providing advanced short courses in high performance computing. The CSC also offers an MSc degree in Scientific Computing.
Research Groups
Fundamentals
Computational work in the natural sciences relies on advances in numerical mathematics, algorithms and computer science. Examples of such “fundamental” research are partial differential equations (PDEs), new strategies for parallel computation, algorithmic approaches to highperformance computing and many more which arise throughout science and engineering.
Molecular Dynamics and Modelling
Broadly, molecular dynamics is concerned with the motion of particles and how that drives many natural processes. In many cases particles are atoms and molecules, which can be used to generate a fundamental understanding of nanomaterial design, of the mechanistic processes in biological membranes, or the formation of biomaterials such as bone. Molecular dynamics is also used to study much larger processes, such as colloids or chromosomes.
Computational Engineering and Fluids
Computational engineering supports almost all branches of traditional engineering. For example, predicting what will happen, quantitatively, when fluids and gases flow, often with the complications of simultaneous flow of heat, mass transfer, chemical reaction (e.g. combustion, rusting), mechanical movement (e.g. of pistons, fans, rudders) stresses.
Monte Carlo and Stochastic Simulation
Monte Carlo methods provide solutions to quantitative problems by inferring from samples produced through stochastic simulation. While the method itself is based on statistical simulation the problems solved can be both deterministic and probabilistic, with applications to all the natural sciences.
Quantum Simulations
Ultimately, quantum mechanics governs how the world around us evolves. Thus we study how quantum effects at the microscopic level manifest themselves in macroscopic behaviour. Applications include photonic materials, organic conductors and chemical reactivity.
Computation of Living Systems
Biology as a quantitative science is increasingly reliant upon on large-scale computational approaches to understand the complex behaviour of living systems. This starts with investigations at the molecular level, continues to models of proteins, bio-polymers and their dynamics and culminates in the simulation of whole habitats.
Research Degrees
Master’s by Research
Duration: 1 year full-time
Doctor of Philosophy (PhD)
Duration: 3 – 3.5 years full-time
In order to adequately support research which transcends traditional departmental boundaries, we offer tailored MSc and PhD degrees which allow more flexibility for both student and supervisor to shape the research agenda. Research opportunities exist in each of our six research groups (see above). Applicants should have, or expect to obtain, a degree in Biology, Chemistry, Computer Science, Engineering, Mathematics, Physics or Statistics. Applicants from closely-related disciplines will also be considered.
Taught Master’s Degree
MSc in Scientific Computing
Duration: 1 year full-time
The MSc programme offers an exciting interdisciplinary course in Scientific Computing, i.e. the use of computers to solve problems in science and engineering. This course is 50% lecture-based, with the other half comprising a research project and dissertation. Examples of advanced modules offered in the course include:
- Foundations of Scientific Computing & Serial Programming Methods
- High Performance Computing
- Computational Linear Algebra
- Practical Algorithms and Data Structures
- Monte Carlo Methods and Computational PDEs
The research project can be in any area of scientific computing. Here, students apply the techniques learnt to real problems in their chosen area of scientific specialisation. Recent graduate destinations include the financial and IT sector. A large proportion of our MSc students continue on a PhD programme in a Science discipline.
Podcast
Research in computer sciences is taking broadcasting in to a new future by enabling the viewer to see three-dimensional images from any angle they choose.
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