UK/EU MPHY4630219 International MPHY4830219
February and October
Applications accepted all year round
The work on this project will seek to determine:
- the detection and classification thresholds whereby the AI accurately detects significant anomalies and their location in 3D
- the timeframe and spatial extent over which events become self-organized
- conditions leading to one event triggering a second
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 Government Doctoral Loan (UK and EU students only).
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.
- You'll need a good first degree from an internationally recognised university (minimum upper second class or equivalent, depending on your chosen course) or a Master’s degree in Medical Engineering, Mechanical Engineering or a similar discipline
- In exceptional cases, we may consider equivalent professional experience and/or Qualifications
- English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0
When you are ready to apply, please follow the 'Apply now' link on the Cosmology and Astrophysics PhD subject area page and select the link for the relevant intake. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV. Our ‘How to Apply’ page offers further guidance on the PhD application process.
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.