Two PhD studentships at the University of Liverpool
I have two open positions for funded studentships at the University of
Applications are open until 10 January 2020.
Follow the links for more detailed versions.
Bringing machine learning techniques to geophysical data processing
The goal of this project is to investigate the use of existing machine learning
techniques to process gravity and magnetics data using the Equivalent Layer
Method. The methods and software
developed during this project can be applied to process large amounts of
gravity and magnetics data, including airborne and satellite surveys, and
produce data products that can enable further scientific investigations.
Examples of such data products include global gravity gradient grids from GOCE
satellite measurements, regional magnetic grids for the UK, gravity grids for
the Moon and Mars, etc.
Large-scale mapping of the thickness of the crust from satellite gravity and gravity gradient data
The goal of this project is to develop improved inversion methods to determine
crustal thickness from gravity and gravity gradient data, in particular
Uieda and Barbosa (2017).
Main objectives are: (1) account for density variation in the oceanic
lithosphere due to temperature; (2) incorporate seismological estimates of
crustal thickness in the inversion process; (3) estimate the density contrast
across the crust-mantle interface in different domains; (4) joint inversion of
gravity and gravity gradient data; (5) develop techniques to reduce the
computational load of the inversion; (6) quantify uncertainty due to errors in
regional crustal and sedimentary basin models. The inversion methods developed
in this project can be applied to produce improved crustal thickness estimates
for South America, Africa, Antarctica, the Moon, Mars, etc.
The funding for these projects comes from the School of Environment Sciences.
Applicants choose a project when applying and will be judged on their own merit
(not the project/supervisor).
There are only a small number of studentships available for the entire School,
so competition for the studentships tends to be high.
Sadly, applications are limited to UK and EU citizens.
Candidates who are able to self-fund (e.g., through their employer) are
encouraged to apply as well. In this case, there is no need to go through the
Both projects have a large computational component. Students will make code
contributions to the different open-source Python software developed by the
Computer-Oriented Geoscience Lab, mainly
Fatiando a Terra.
They will be trained to develop software in a collaborative environment using
GitHub and use the current best practices in software engineering and
Applicants are encouraged to read the
lab manual to familiarize themselves with
the way we approach science, expectations, our code of conduct, etc.
If you’re interested in applying (or know someone who might be), please
get in touch!