PhD student position based at Chalmers University of Technology, funded by WASP and the Wallenberg Centre for Quantum Technology (WACQT).
About the position
Variational quantum algorithms (VQAs) seek to make the most of noisy intermediate-scale quantum (NISQ) devices currently operating at academic and industrial labs around the world. VQAs are hybrid algorithms where NISQ devices are controlled via optimization algorithms implemented on classical computers. VQA algorithms have promising near-term applications including in quantum chemistry and optimization.
The application of VQAs to quantum chemical problems is currently limited by both software and hardware – in this project the selected candidate will address two key limitations on the software side:
– Warm-start for VQAs using the underlying structure of molecules and their Hamiltonians – to minimize the number of quantum-classical computer cycles needed for convergence.
– Learning functions to map molecules to bespoke hardware-efficient circuit Ansätze – to lower the demand on the number of qubits necessary to accurately compute ground state energies.
The selected candidate will be embedded into an interdisciplinary environment between the Chalmers departments of Computer Science and Engineering as well as Chemistry and Chemical engineering, and the Wallenberg Centre for Quantum Technology (WACQT). This inter-disciplinary research project is part of an on-going collaboration between the groups of Simon Olsson, Anton Frisk Kockum, and Martin Rahm to enable quantum chemistry on quantum computers aided by machine learning. The selected candidate will be based at the Computer Science and Engineering department yet enjoy full access to and a work-place at WACQT and the Chemistry and Chemical Engineering departments.