Ph.D Studentship in Reliable Probabilistic Mechanistic Learning

Join a collaborative Ph.D project to develop a trustworthy AI facility in Petrophysics, working on fast and easy prediction of rock sample properties using NMR observations.

Join a collaborative Ph.D project between the University of York and Weatherford International to develop a trustworthy AI facility in Petrophysics.

As a Ph.D student, you will work on fast and easy, closed-form prediction of proportions and other identifying properties of rock samples using Nuclear Magnetic Resonance (NMR) observations.

• Undertake probabilistic supervised learning of the matrix-valued function representing the relationship between petrological compositional parameters and NMR observables.
• Generate a training dataset using a new Bayesian methodology.
• Predict the matrix of petrological compositional parameters of a new rock sample and encode this predictive facility as a data-driven AI tool.

Apply online via the PhD and MPhil in Mathematics website here before 10th February, 2025.

Tags: PhD studentship, probabilistic mechanistic learning, trustworthy AI facility, Petrophysics, Nuclear Magnetic Resonance, Bayesian methodology, data-driven AI tool