Dark Matter is one of the main puzzles in fundamental physics and Weakly Interacting Massive Particles (WIMP) are among the best-motivated dark matter particle candidates. As of today, the most sensitive experimental technique to discover the WIMPs in the mass range from 1 GeV/c2 to 10 TeV/c2 is the dual phase Time Projection Chamber (TPC) filled with noble liquids. The “dual-phase” approach has the main advantage to provide simultaneous access to the ionization and to the scintillation signals. This enables accurate reconstruction of the event topology and powerful discrimination between electronic and nuclear recoils, the latter being the signal expected from WIMP dark matter candidates. These features, together with the scalability to massive detectors, make liquid argon (LAr) a compelling target for WIMPs of mass >20 GeV/c2. 

DarkSide-20k is a 50 tons LAr detector currently under construction at Laboratori Nazionali del Gran Sasso in Italy expected to start the data taking in 2027. As part of the DarkSide program, the APC team coordinates data reconstruction, simulation, and sensitivity studies. The APC team has developed a highly optimized python-based data reconstruction framework for the next-generation DarkSide-20k experiment.

DarkSide-20k can significantly extend its physics reach by exploiting the ionization channel alone, thereby lowering the detection threshold. This opens new opportunities to search for very light dark matter candidates as well as neutrinos from the Sun and from core-collapse supernovae. In this context, the APC team led the analysis that set the world’s best limits on low-mass WIMPs using data from the 50-kg LAr DarkSide-50 experiment, and evaluated the sensitivity of DarkSide-20k to supernova neutrinos.

To further enhance these sensitivities, it is essential to reduce uncertainties in the modeling of the liquid argon (LAr) response to nuclear recoils. The APC team, in collaboration with the University of São Paulo (USP, Brazil), is addressing these uncertainties using small-scale setups exposed to neutron sources in controlled environments. The ARIS experiment, led by APC, provided critical insights into the LAr response at low energies using a monochromatic neutron beam from the LICORNE source at ALTO (Orsay). APC and USP are currently playing a leading role in the ReD experiment, a TPC exposed to ²⁵²Cf fission neutrons, designed to probe the LAr response in the keV range. A new data campaign is planned for 2026 to expose ReD to a DD neutron generator at LNS (Italy).

The PhD candidate will focus on extending the physics reach of DarkSide-20k to “light” signals, such as those induced by light dark matter particles and supernova neutrinos. The work will involve improving the LAr response model by contributing to the data taking, simulation, and analysis of ReD with both ²⁵²Cf and DD neutron sources. In parallel, the candidate will use Monte Carlo simulations to assess the feasibility of probing the sub-keV response using the ALTO accelerator. A key objective will be to evaluate the impact of the improved response model on existing DarkSide-50 limits and on the projected sensitivity of DarkSide-20k. The candidate will also take part in the development of DarkSide-20k data reconstruction, with a particular emphasis on ionization signals, using advanced supervised algorithms.

In the first year, the candidate will focus on analyzing ReD data and participating in the upcoming data campaign using the DD neutron source. In parallel, they will investigate how uncertainties in the LAr response model impact the sensitivity of DarkSide-20k.

In the second year, the candidate will complete the ReD data analysis and integrate the improved response model into the DarkSide-50 and DarkSide-20k sensitivity frameworks. At the same time, they will study the backgrounds relevant to the low-mass dark matter search region and develop appropriate rejection strategies.

In the third year, the candidate will determine the sensitivities to various light signals. This phase will coincide with the beginning of DarkSide-20k data acquisition. Having acquired expertise in event reconstruction, selection criteria, and sensitivity tools, the candidate will contribute to the analysis of the first DarkSide-20k data.

Expertises in C++ and Python programming, and in particle physics data analysis are appreciated.

This PhD is funded within the framework of a collaborative program between APC and USP.