Careers and PhD Opportunities

Vacancies

Research Fellow - University of Warwick

2 year fixed term

£35,608 to £46,049

Deadline: 12 February 2026

The Diamond Research Groups within the Departments of Physics and Chemistry at the University of Warwick seek to appoint a Research Fellow to drive the development of a diamond-based quantum sensing platform as part of the UK Quantum Biomedical Sensing Research Hub.

The role will include the development and fabrication of novel diamond-based quantum sensing platforms, based on integrated nano- and micro-pores, for environmental and biomedical analysis on the micro- and nanoscale, and associated equipment construction and operation. The appointment is for two years with the possibility of extension as part of the 5-year Q-BIOMED project.

We are looking for someone with a PhD in Physics, Nanotechnology, Electrochemistry, Engineering or a related field, or someone who is very close to obtaining this.

You should ideally have a background in building and/or running chemistry/physics experiments, magnetic resonance, microfluidics / nanopores, electrochemistry, nanofabrication, materials science, NV centres and/or quantum technology.

For informal queries, please contact Professor Mark Newton: m.e.newton@warwick.ac.uk

Funded PhD/postdoc secondment to work on ML/Bayesian methods for quantum biomedical sensing

Quantum sensors leverage quantum mechanical effects to probe their environment. Nitrogen-vacancy (NV) centres in diamond are optically addressable spins that are sensitive to magnetic noise, charge, electromagnetic fields, temperature, and pressure, promising impactful sensing methods for biophysics and diagnostics.

We are offering a fully funded 2-3 month secondment at the London Centre for Nanotechnology (UCL), for either a PhD student or a postdoc, to work on two applications of machine learning and Bayesian methods in quantum sensing aimed at improving sensitivity. The project is part of the Q-BIOMED Biomedical Quantum Sensing Hub and is a collaboration between Benjamin Miller (UCL) and Cristian Bonato (Heriot-Watt University).

Funding model

• PhD students: You will temporarily pause your current studentship and be paid as a Research Assistant (UCL Grade 6) for the duration of the secondment. Your original PhD funding will be extended.

• Postdocs: You will be funded at your current salary level, with potential to extend your existing funding (subject to funding).

Project themes

(i) Machine-learning-enhanced readout for NV-based diagnostics: Previous work in our group has shown a 10^5-fold improvement in the fundamental sensitivity over gold nanoparticles in rapid diagnostic tests and a 2-day diagnostic advantage for SARS-CoV-2 detection. However, there remains a 10–100× gap between the fundamental and real-world diagnostic sensitivities. We will apply neural networks and spatial Fourier transforms to classify spatiotemporal assay data.

(ii) Bayesian and adaptive methods for NV-based sensing: current work on coherent sensing protocols is limited by SNR. Building on work by Bonato et al. you will use Bayesian updating to extract spectral parameters from noisy time-domain signals, and implement or simulate real-time adaptive measurement strategies to optimise acquisition and reduce experiment time.

We are keen to hear from students/postdocs with experience in one or more of:

• Machine learning (especially for image or time-series data)

• Bayesian inference / statistical signal processing

• Python (preferred) or similar for data analysis

and a desire to gain some knowledge of quantum sensing.

The bulk of the project is data analysis and simulation. There is also scope for hardware/experiment control if it progresses to real time demonstrations.

Please get in touch with Ben Miller: ben.miller@ucl.ac.uk if you are interested in applying.