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The SBND (Short-Baseline Near Detector) experiment is part of the multi-detector Short Baseline Neutrino (SBN) programme located along the Booster Neutrino Beamline at Fermilab, USA. Each detector in the SBN programme utilises the liquid argon time projection chamber (LArTPC) technology. The main goal of the SBN programme is to address a number of anomalies observed by previous short baseline experiments through searches for sterile neutrinos and additional beyond the Standard Model (BSM) phenomena. SBND will also study the intricate nature of neutrino interactions on heavy nuclei in great detail, which will be invaluable to the next generation of liquid argon neutrino detectors.
The particle physics and particle astrophysics (PPPA) group at the University of Sheffield is involved in both the SBND and SBN projects, with a broad range of responsibilities spanning detector construction and modelling, software development, and data analysis.
This PhD project will focus on addressing the short baseline anomalies through measurements of key parameters which govern sterile neutrino oscillations and BSM processes. This will involve taking a lead role in developing dedicated software frameworks, including the implementation of machine learning techniques. Ultimately, the software will be used to process and analyse large simulated and real physics datasets.
A long-term attachment (6-12 months) and short-term travel to Fermilab during the first operations of SBND will be possible, as well as partaking in detector operation shifts.
The candidate should have a good knowledge of particle physics and experience programming in Python or C++.
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