We offer an 18-months post-doctoral position for a motivated researcher to join our work on the application of machine learning to quantum sensing and imaging. This research is funded by the UK Quantum Enhanced Imaging hub. The researcher is expected to design and benchmark algorithms to optimise quantum sensing and imaging with single electron spins, for application to magnetic field imaging and nanoscale magnetic resonance. While the position is theoretical/numerical in nature, we expect the candidate to work proficiently with experimentalists to implement the proposed algorithms.
Where: the research will be carried out at Heriot-Watt University (Edinburgh) under the supervision of Prof Cristian Bonato (experimental physicist), Dr Yoann Altmann (applied mathematician) and Dr Erik Gauger (theoretical physicist).
Who: we are looking for a researcher with a passion for experimental science and a background in quantum technology and/o machine learning. We are looking for candidates to start as soon as possible.
Please contact Dr Cristian Bonato (c.bonato@hw.ac.uk) for inquiries (as soon as possible). The application link is here (deadline 11th December 2022).
Relevant publications. Please check the following publications for some ideas about the research:
(1) MJ Arshad et al, "Online adaptive estimation of decoherence timescales for a single qubit", arXiv:2210.06103 (2022)
(2) I Zohar et al, "Real-time frequency estimation of a qubit without single-shot-readout", arXiv:2210.05542 (2022)
(3) V Gebhart et al, "Learning Quantum Systems", arXiv:2207.00298 (2022)
(4) E Scerri et al, "Extending qubit coherence by adaptive quantum environment learning", New Journal of Physics 22 035002 (2020)
(5) C. Bonato et al, "Optimized quantum sensing with a single electron spin using real-time adaptive measurements", Nature Nanotechnology 11, 247-252 (2016)
