"Application Of Gan Techniques For Efficient Analysis Of Large Amounts Of Data From Particle Ac[] Foggia

"Application Of Gan Techniques For Efficient Analysis Of Large Amounts Of Data From Particle Ac[]
Foggia
Puglia, Foggia

Organisation/Company: Università di Foggia Research Field: Physics Researcher Profile: Recognised Researcher (R2), Leading Researcher (R4), First Stage Researcher (R1), Established Researcher (R3) Country: Italy Application Deadline: 5 Mar 2025 - 23:59 (UTC) Type of Contract: To be defined Job Status: Not Applicable Is the job funded through the EU Research Framework Programme? Other EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The research activity will initially focus on identifying the GAN network best suited to reproduce the physical characteristics of the rare or exotic particle of interest and its daughter particles (e. g. , kinematic distributions, decay topology) produced in central Pb-Pb collisions. Next, an alternative analysis model will be designed that, starting from the synthetic data generated by GANs, can improve the supervised learning of further machine learning algorithms and optimize I/O on large amounts of real data. Eligibility of fellows: country/ies of residence: EUROPE Eligibility of fellows: nationality/ies: J-18808-Ljbffr