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| Funder | Science and Technology Facilities Council |
|---|---|
| Recipient Organization | University of Sussex |
| Country | United Kingdom |
| Start Date | Sep 30, 2024 |
| End Date | Mar 30, 2028 |
| Duration | 1,277 days |
| Number of Grantees | 2 |
| Roles | Student; Supervisor |
| Data Source | UKRI Gateway to Research |
| Grant ID | 2917837 |
Exotic scenarios providing viable solutions to experimental evidence that is inconsistent with the Standard Model of particle physics (e.g., the existence of dark matter in our universe, or the so-called "g-2" anomaly) will be explored using LHC Run-2 and Run-3 data using the golden "multileptonic signatures", whereby proton-proton collisions yield at least two electrons, muons, or taus in the final state.
Signal-to-background selections will be optimised using powerful data mining and machine learning techniques.
In addition, there will be an opportunity to participate, at an adequate level, in broader-interest core experimental activities of the ATLAS experiment, such as triggering (including in view of the high-luminosity LHC upgrade), the study of the combined physics performance of the ATLAS detector, and experimental operations at CERN.
University of Sussex
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