The task of Decoding the Fundamental Theory of Nature is the central task for modern particle physics but it can only be solved by using advanced computing strategy and techniques. Many promising models have been suggested for the Physics Beyond the Standard Model (BSM) , however no generic approach on mapping between different theories and Particle physics data has been proposed.
This project will develop further High Energy Physics Model Database https://hepmdb.soton.ac.uk/ the novel project created at the HEP group ofUniversity of Southampton http://www.hep.phys.soton.ac.uk/ and will highly involve application and development of new computational methods and strategies, including Markov Chain Monte Carlo techniques combined with complicated statistical analysis tools, implementation of Neural-Net analysis.
Besides, the proposed project will develop new ideas related to implementation of fast Monte-Carlo simulation and Symbolic Matrix element evaluation using multi-threading techniques. These new techniques would allow exploration new models in real time i.e. spending seconds or minutes instead of days or weeks. At the same time an important element of the project is an effective comparison between simulated and real data. This non-trivial task will be heavily relying on MPI/OpenMP/GPU parallelisation.
This project and involved student will greatly benefit from development of new computing approaches mentioned above proving crucial crucial interdisciplinary role of new developments in computing and large data techniques applied to physics.We are looking for an applicant with a background in Particle Physics and Computing and an appetite to learn and research across conventional discipline boundaries. The stipend is at the standard EPSRC levels. More details on facilities and computing equipment are available http://ngcm.soton.ac.uk/facilities.html
If you wish to discuss any details of the project informally, please contact Prof. Alexander Belyaev, Email: [email protected]