Thermodynamic cost of Quantum Extreme Learning Machines

Researcher (R4), First Stage Researcher (R1), Established Researcher (R3) Application Deadline: 31 Oct 2026 - 23:59 (UTC) Country: Italy Type of Contract: To be defined Job Status: Not Applicable Is the job funded through the EU Research Framework Programme?: Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure?: No Offer Description Extreme Learning Machines (ELMs) are feed-forward neural networks with a single hidden layer and random couplings, trained via linear regression, saving time and resources. Their quantum counterparts (QELMs) use a quantum reservoir to build complex representations of classical data, with inexpensive, noise-robust performance. The Quantum Theory Group at UNIPA has demonstrated the advantages of QELMs for validating and certifying quantum systems without tomographic reconstruction. These algorithms apply to the optimisation of complex processes, quantum and classical, on NISQ machines, to the energetic characterisation of biochemical systems simulated on quantum computers, and to the optimisation of networks for communication and logistics. The research will analyse the thermodynamic cost of QELMs to establish their energetic sustainability, using quantum information thermodynamics, a field in which the group is a pioneer. Where to apply E-mail: pec@cert.unipa.it Requirements Additional Information Eligibility criteria Eligible destination country/ies for fellows: Italy Eligibility of fellows: country/ies of residence: EUROPE OTHER Eligibility of fellows: nationality/ies: EUROPE OTHER Website for additional job details: https://www.unipa.it/albo.html Work Location(s) Number of offers available: 1 Company/Institute: Università degli Studi di Palermo Country: Italy Contact City: Palermo Website: https://www.unipa.it/servizi/assegnidiricerca/incarichi-post-doc/