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Expertise / Recherche : Quantum Machine Learning H/F (2022-44276)

Palaiseau, Île-de-France À partir du 14/01/22 6 mois
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The design of Parameterized Quantum Circuits is one of the most promising approach to get something close to neural networks on quantum computers. However these PQC are a succession of linear gates. Some work to get non linearity have been proposed. For example, Schuld, Sinayskiy, and Petruccione 2014 obtain non-linearity with the help of the measurement process while Tacchino et al.2019 do not rely on the measurement process to get non linearity.

We propose to investigate these attempts on various taks such as classification and RL. The successful candidate will have the possibility to do a PhD thesis related to this field after the internship.

Formation : niveau M2 / DEA ou 3ème année école d’ingénieurs,

Compétences requises : Strong Mathematical background, Quantum Computation, Experience in Cirq or Qiskit, Machine Learning is a plus