The Berlin Mathematics Research Center MATH+ sets out to advance mathematics itself and its interdisciplinary power with the aim of achieving progress on grand challenges in a wide variety of application fields.
MATH+ will start with nine major units for project-oriented research: four Application Areas and five Emerging Fields. In both, mathematicians from a wide range of different disciplines collaborate – with each other and with leading researchers from diverse application fields as well as representatives from industry. These Research Units are complemented by Transfer Units designed for translational research. For further details please visit www.mathplus.de.
In the frame of the Cluster of Excellence, MATH+ project EF1-7 “Quantum machine learning” is looking for a research assistant. Recently the highly interdisciplinary field of quantum machine learning has emerged and enjoyed significant interest. In this new field, both the underlying foundations of statistical learning theory and the associated applied machine learning techniques have begun to be extended to the setting of both quantum algorithms and data-sets emerging from a quantum context. In particular, exciting proof-of-principle algorithms and results have been obtained in all three newly emerging branches of this rapidly developing field. In particular, the application of classical learning algorithms to data-sets of a quantum origin (classical-quantum) has yielded new techniques for decoding of topological quantum error correcting codes, the identification of phases and the design of novel experiments.
Simultaneously, new quantum algorithms, for essential learning-sub routines such as matrix inversion and gradient descent, have been developed for application to classical data (quantum-classical), and finally, in the quantum-quantum context, in which quantum algorithms are applied to quantum data-sets while there are still many open questions, recent years have seen advances such as the development of a novel reinforcement learning framework for quantum agents in quantum environments. The goal of this project is to establish a mathematical methodology for instances of quantum machine learning, understanding its statistical basis, and at the same time to explore practical applications.
MSc in physics, computer science or mathematics.
A research background in applied mathematics or theoretical physics is highly desired. It will also be helpful to have experience in coding. A PhD degree would be advantageous.
All application quoting the reference code should be addressed to Prof. Dr. Jens Eisert: firstname.lastname@example.org or postal to
Freie Universität Berlin
Fachbereich Mathematik und Informatik
Institut für Mathematik
Herrn Prof. Dr. Jens Eisert
14195 Berlin (Dahlem)