The Geotechnical Research Group at Northumbria University, Newcastle upon Tyne, UK is looking for a highly motivated and talented individual to fill a Ph.D. student position. To keep pace with the rapidly developed digital technologies, the project will perform data analytics of geotechnical and geophysical data using novel machine learning methods, with a focus on dealing with large quantities of multivariate, incomplete, 3-dimensional data subject to spatial variability.

The objective of the project is to develop a three-dimensional spatially variable geological profile with a reasonable quantification of the uncertainties. Various machine-learning methods will be explored to make the geological model explicit (i.e., to be not a black box) and incorporate human knowledge and judgment. The student will be supervised by data analytic, geotechnical and geophysical experts in the team and have the opportunity to cooperate with leading researchers in the field of data analytics in geoengineering. The student will work closely with industry partners to deal with geological modeling challenges in geologically complex areas.

More information can be found on the following link: https://www.findaphd.com/phds/project/data-driven-site-characterization-using-geotechnical-and-geophysical-data-rdf23-mce-qi/?p151500