machine learning

Applications are invited for a postdoctoral research position with a possibility for extension, in the field of theory of quantum computations and quantum algorithms. The position will be held at Skolkovo Institute of Science and Technology (Skoltech), Moscow, Russia. The start date is flexible.
The successful applicant will work in the research group led by Prof Jacob Biamonte in the area of quantum computations and quantum networks, with a focus on quantum enhanced algorithms and error mitigation on experimental devices.

A three-year PhD studentship (comprising stipend and fees) is available to international students to work with Alessandro Ferraro and Mauro Paternostro at the Quantum Technology group, School of Mathematics and Physics, Queen's University Belfast.

The project will focus on the use of machine learning techniques for quantum information processing, with particular emphasis on quantum state and process engineering in photonics quantum networks.

Research in the group focuses on out-of-equilibrium quantum dynamics to study problems at the interface of condensed matter, AMO, and statistical physics. To investigate the far-from-equilibrium behavior of many-body systems, we will be developing both analytical understanding and computational tools at the interface of quantum mechanics and machine learning. We are collaborating with leading experimental and theoretical groups in the field.

We are currently looking for a highly motivated and skilled postdoc/experienced researcher to join the new Quantum Many-Body Dynamics group at Sofia University. We are interested in a broad range of topics revolving around the field of quantum many-body systems [non-equilibrium quantum dynamics, condensed matter theory (phase transitions, critical phenomena), AMO physics, and statistical physics], developing techniques and ideas from Deep Learning for quantum systems.

We are currently looking for highly motivated and skilled PhD students to join the new Quantum Many-Body Dynamics group at Sofia University. We are interested in a broad range of topics revolving around the field of quantum many-body systems [non-equilibrium quantum dynamics, condensed matter theory (phase transitions, critical phenomena), AMO physics, and statistical physics], developing techniques and ideas from Deep Learning for quantum systems.

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