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Applications are invited for a self-funded, 3 year full-time or 6 year part-time PhD project, to commence in October or February.

This PhD will be based in the Institute of Cosmology and Gravitation and will be supervised by Dr Andrew Lundgren, Dr Philip Benson and Professor David Bacon.

Laboratory simulations offer a dynamic and flexible route to testing and verifying a numerical models and observations in the physical sciences. For example: in the Earth sciences, high force hydraulic presses are routinely used to simulate earthquakes under simulated stresses, collecting acoustic emission (the laboratory analogue to tectonic seismic data) using an embedded array of sensors that collectively generate 830 Gb/Hr (0.23 Gb/s) in the form of waveforms.

Within astronomy, observatories like the Laser Interferometer Gravitational wave Observatory (LIGO) and large cosmology surveys also generate data rates up to 1 Gb/s. In both cases a common challenge is that the vast wealth of continuous data cannot be adequately processed for events embedded in the medium by direct user intervention, due to these high data rates.

Instead, the data requires processing without knowing where events will occur or even exactly what they look like. Machine learning and AI provide exciting new methods for detecting transient events (whether earthquakes or supernovae).

To address this challenge, the controlled conditions of the rock physics laboratory will be used to compress a medium to failure, generating a stream of data containing events analogous to supernovae embedded in a transmissive medium. Data will be analyzed using a new range of AI algorithms, but with the advantage of allowing post-test comparisons to the final “sample” and with respect to a range of conditions or materials.

Success on this project will lead to new tools across a range of physical sciences, ranging from the science of Earthquake localization, to fundamental questions relating to the evolution of the universe via LIGO and other new, expensive, observatories.

Fees and funding

Visit the research subject area page for fees and funding information for this project.

Funding availability: Self-funded PhD students only. 

PhD full-time and part-time courses are eligible for the UK  (UK and EU students only).

Bench fees

Some PhD projects may include additional fees – known as bench fees – for equipment and other consumables, and these will be added to your standard tuition fee. Speak to the supervisory team during your interview about any additional fees you may have to pay. Please note, bench fees are not eligible for discounts and are non-refundable.

How to apply

We’d encourage you to contact Dr. Andrew Lundgren (andrew.lundgren@port.ac.uk) to discuss your interest before you apply, quoting the project code.

Please note: to be considered for this self-funded PhD opportunity you must quote project code MPHY4630219 UK/EU students and MPHY4830219 International students when applying.